diff --git a/examples/coordination/examples.ipynb b/examples/coordination/examples.ipynb
index 89dac3bd..3844bdc1 100644
--- a/examples/coordination/examples.ipynb
+++ b/examples/coordination/examples.ipynb
@@ -38,7 +38,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {
     "collapsed": true
    },
@@ -47,7 +47,7 @@
     "# OPTION 1: DOWNLOAD CORPUS\n",
     "# UNCOMMENT THESE LINES TO DOWNLOAD CORPUS\n",
     "# DATA_DIR = '<YOUR DIRECTORY>'\n",
-    "# ROOT_DIR = convokit.download('wiki-corpus', data_dir=DATA_DIR)\n",
+    "# ROOT_DIR = download('wiki-corpus', data_dir=DATA_DIR)\n",
     "\n",
     "# OPTION 2: READ PREVIOUSLY-DOWNLOADED CORPUS FROM DISK\n",
     "# UNCOMMENT THIS LINE AND REPLACE WITH THE DIRECTORY WHERE THE CORPUS IS LOCATED\n",
@@ -58,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "collapsed": true
    },
@@ -115,7 +115,36 @@
    "metadata": {
     "collapsed": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Created chart \"Target-admins vs Target-nonadmins.png\"\n",
+      "Created chart \"Speaker-admins vs Speaker-nonadmins.png\"\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# create coordination object\n",
     "coord = Coordination()\n",
@@ -163,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "collapsed": true
    },
@@ -186,7 +215,7 @@
     "# OPTION 1: DOWNLOAD CORPUS\n",
     "# UNCOMMENT THESE LINES TO DOWNLOAD CORPUS\n",
     "# DATA_DIR = '<YOUR DIRECTORY>'\n",
-    "# ROOT_DIR = convokit.download('supreme-corpus', data_dir=DATA_DIR)\n",
+    "# ROOT_DIR = download('supreme-corpus', data_dir=DATA_DIR)\n",
     "\n",
     "# OPTION 2: READ PREVIOUSLY-DOWNLOADED CORPUS FROM DISK\n",
     "# UNCOMMENT THIS LINE AND REPLACE WITH THE DIRECTORY WHERE THE CORPUS IS LOCATED\n",
@@ -197,7 +226,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {
     "scrolled": true
    },
@@ -333,7 +362,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {
     "collapsed": true
    },
@@ -341,12 +370,12 @@
    "source": [
     "case_ids = {'03-1164', '04-1332', '04-1140', '04-805', '04-1495', '05-352', '04-1360b', '06-5306', '03-1388', '04-473b', '03-8661', '03-1160', '03-633', '05-1508', '05-746', '05-547', '05-502', '04-759', '03-1116', '05-1240', '03-287', '04-607', '05-1126', '04-1477', '04-8990', '06-480', '04-1152', '05-1429', '03-1488', '04-10566', '04-905', '05-493', '05-1575', '04-848', '05-983', '03-1395', '06-5754', '04-52', '05-9264', '03-725', '05-184', '04-1131', '04-698', '05-381', '06-593', '02-1472', '04-712', '04-1376', '03-184', '06-116', '04-1618', '03-1500', '03-9627', '05-669', '05-85', '05-7058', '06-313', '05-1631', '05-6551', '04-1244', '05-705', '06-84', '03-1693', '04-593', '04-1034', '04-944', '04-1186', '05-1342', '04-277', '04-37', '04-70', '06-219', '04-1329', '05-465', '05-595', '04-631', '03-1230', '06-278', '04-473', '05-130', '03-814', '04-1414', '04-433', '05-83', '04-637', '04-1327', '03-9685', '02-1672', '03-1696', '04-1170b', '03-636', '04-1371', '05-1272', '04-6964', '05-380', '05-996', '03-1407', '05-1256', '05-998', '03-932', '06-5247', '04-1067', '05-1157', '03-923', '05-1541', '05-9222', '05-5992', '03-9168', '05-200', '05-260', '04-368', '04-603', '05-204', '04-480', '04-1528', '04-721', '03-10198', '04-495', '03-878', '03-9877', '04-1527', '05-593', '04-1506', '05-128', '06-5618', '05-1074', '03-9560', '03-892', '04-1084', '04-980', '05-7053', '04-881', '03-1237', '04-1324', '05-416', '04-5928', '05-1629', '04-5293', '03-9046', '04-163', '05-5705', '03-1293', '04-1581', '04-597', '04-169', '03-1423', '03-407', '03-750', '05-1056', '03-388', '05-5224', '03-931', '03-1238', '04-1203', '03-1454', '05-259', '05-11284', '05-8820', '05-608', '04-1739', '06-102', '04-5462', '03-855', '03-1039', '04-514', '04-563', '05-11304', '05-8794', '04-623', '04-885', '04-1170', '05-1589', '04-9728', '06-157', '04-5286', '04-1264', '05-908', '04-1704', '05-848', '04-1350', '05-1120', '03-409', '06-484', '04-1144', '05-785', '03-1601', '04-6432', '04-373', '04-1544', '04-278', '05-409', '05-5966', '04-928', '05-1382', '05-915', '05-1345', '128orig', '04-340', '03-1566', '05-18', '105original', '03-9659', '04-1360', '03-710'}\n",
     "\n",
-    "corpus = corpus.filter_utterances_by(lambda u: u.meta[\"case_id\"][5:] in case_ids)"
+    "corpus = corpus.filter_utterances(corpus, lambda u: u.meta[\"case_id\"][5:] in case_ids)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -359,26 +388,22 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -483,7 +508,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.9.0"
   }
  },
  "nbformat": 4,
diff --git a/examples/dataset-examples/wikiconv/Create_Conversations_Script.ipynb b/examples/dataset-examples/wikiconv/Create_Conversations_Script.ipynb
index 3264372b..82666aeb 100644
--- a/examples/dataset-examples/wikiconv/Create_Conversations_Script.ipynb
+++ b/examples/dataset-examples/wikiconv/Create_Conversations_Script.ipynb
@@ -31,8 +31,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Downloading wikiconv-2003 to /kitchen/convokit_corpora_jpc/wikiconv-2003\n",
-      "Downloading wikiconv-2003 from http://zissou.infosci.cornell.edu/convokit/datasets/wikiconv-corpus/corpus-zipped/2003/full.corpus.zip (38.7MB)... Done\n"
+      "Dataset already exists at /Users/seanzhangkx/.convokit/downloads/wikiconv-2003\n"
      ]
     }
    ],
@@ -133,7 +132,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[Conversation({'obj_type': 'conversation', 'meta': {'page_id': '383784', 'page_title': 'Matty j', 'page_type': 'user_talk'}, 'vectors': [], 'tree': None, 'owner': <convokit.model.corpus.Corpus object at 0x7f0d5a31d390>, 'id': '2081953.389.389'}), Conversation({'obj_type': 'conversation', 'meta': {'page_id': '187772', 'page_title': 'Large numbers', 'page_type': 'talk'}, 'vectors': [], 'tree': None, 'owner': <convokit.model.corpus.Corpus object at 0x7f0d5a31d390>, 'id': '1053969.145.145'}), Conversation({'obj_type': 'conversation', 'meta': {'page_id': '269015', 'page_title': 'Creationism/Archive 6', 'page_type': 'talk'}, 'vectors': [], 'tree': None, 'owner': <convokit.model.corpus.Corpus object at 0x7f0d5a31d390>, 'id': '1324714.25382.25382'})]\n"
+      "[Conversation({'obj_type': 'conversation', 'vectors': [], 'tree': None, 'owner': <convokit.model.corpus.Corpus object at 0x7fe2586ef280>, 'id': '1172638.641.641', 'meta': ConvoKitMeta({'page_id': '253576', 'page_title': 'Roman Catholic Archdiocese of Quebec', 'page_type': 'talk'})}), Conversation({'obj_type': 'conversation', 'vectors': [], 'tree': None, 'owner': <convokit.model.corpus.Corpus object at 0x7fe2586ef280>, 'id': '691102.8439.8439', 'meta': ConvoKitMeta({'page_id': '178863', 'page_title': 'Jimfbleak', 'page_type': 'user_talk'})}), Conversation({'obj_type': 'conversation', 'vectors': [], 'tree': None, 'owner': <convokit.model.corpus.Corpus object at 0x7fe2586ef280>, 'id': '490071.18706.18706', 'meta': ConvoKitMeta({'page_id': '14218', 'page_title': 'Homophobia/Archive 6', 'page_type': 'talk'})})]\n"
      ]
     }
    ],
@@ -164,9 +163,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "https://en.wikipedia.org/w/index.php?title=user_talk:Matty_j\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:Large_numbers\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:Creationism/Archive_6\n"
+      "https://en.wikipedia.org/w/index.php?title=talk:Roman_Catholic_Archdiocese_of_Quebec\n",
+      "https://en.wikipedia.org/w/index.php?title=user_talk:Jimfbleak\n",
+      "https://en.wikipedia.org/w/index.php?title=talk:Homophobia/Archive_6\n"
      ]
     }
    ],
@@ -309,16 +308,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Original Order of IDs:['2081953.413.389', '2081953.389.389']\n",
-      "Correct Order of IDs:['2081953.389.389', '2081953.413.389']\n",
+      "Original Order of IDs:['1172638.641.641', '1173000.1045.1045']\n",
+      "Correct Order of IDs:['1172638.641.641', '1173000.1045.1045']\n",
       "\n",
       "\n",
-      "Original Order of IDs:['1053969.145.145', '1054046.1046.1046', '1054707.1680.1680', '3744612.1995.1995']\n",
-      "Correct Order of IDs:['1053969.145.145', '1054707.1680.1680', '3744612.1995.1995', '1054046.1046.1046']\n",
+      "Original Order of IDs:['811685.0.8439', '811685.0.8612']\n",
+      "Correct Order of IDs:['811685.0.8439', '811685.0.8612']\n",
       "\n",
       "\n",
-      "Original Order of IDs:['1344757.132.30543', '1344757.132.30573', '1344757.132.30760', '1344757.132.31076', '1344757.132.30860', '1344757.132.31731', '1344757.132.32775', '1344757.132.32926', '1329814.35766.35766']\n",
-      "Correct Order of IDs:['1344757.132.30543', '1344757.132.30573', '1344757.132.30760', '1344757.132.31076', '1344757.132.30860', '1344757.132.31731', '1344757.132.32775', '1344757.132.32926', '1329814.35766.35766']\n",
+      "Original Order of IDs:['709021.8491.9368', '709021.8654.11099']\n",
+      "Correct Order of IDs:['709021.8491.9368', '709021.8654.11099']\n",
       "\n",
       "\n"
      ]
@@ -358,7 +357,7 @@
     "            if (utterance_value.text != \" \"):\n",
     "                print (utterance_value.text)\n",
     "                date_time_val = datetime.fromtimestamp(utterance_value.timestamp).strftime('%H:%M %d-%m-%Y')\n",
-    "                formatted_user_name = \"--\" + str(utterance_value.user.name) + \"  \" + str(date_time_val)\n",
+    "                formatted_user_name = \"--\" + str(utterance_value.speaker.id) + \"  \" + str(date_time_val)\n",
     "                print (formatted_user_name)\n",
     "        print ('\\n\\n')"
    ]
@@ -372,42 +371,28 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "https://en.wikipedia.org/w/index.php?title=user_talk:Matty_j\n",
-      " Baseball/temp \n",
-      "--Ktsquare  20:56 23-12-2003\n",
-      "Hi Matty, I noticed you have contributed to many bios of MLB players, I'd like to ask for your opinion whether it's time to move the rewritten Baseball/temp to Baseball. Please comment at Talk:Baseball/temp. Thanks.  \n",
-      "--Ktsquare  20:56 23-12-2003\n",
+      "https://en.wikipedia.org/w/index.php?title=talk:Roman_Catholic_Archdiocese_of_Quebec\n",
+      "Two problems with the title:\n",
+      "1) it should not be capitalized;\n",
+      "2) all the archbishops are also bishops (for example, the list at Diocese de Montreal lists a particular one as \"third bishop and first archbishop\").\n",
+      "I had moved this to List of Roman Catholic bishops of Quebec, and likewise for the Montreal list, but efghij moved them back. May I ask why? - \n",
+      "--Montrealais  11:41 20-07-2003\n",
+      "1) It should be capitalized. \"Bishop of Quebec\" is a title, just like \"Prime Minister of Canada\" or \"King of Spain\".\n",
+      "2) It's technically correct that all archbishops are also bishops, however it is somewhat counter-intuatve to list them all under \"Bishops of Quebec\".\n",
+      "-  19:00 20 Jul 2003 (UTC)\n",
+      "--Efghij  15:00 20-07-2003\n",
       "\n",
       "\n",
       "\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:Large_numbers\n",
-      "Can I suggest that we include only pure numbers in this article, not distances and other measurements?  Would anyone object if I deleted the astronomical distances, since they are only large numbers when expressed in small units?  I suppose I should go further and say that Avogradro's number is also just an arbitrary unit, but I shan't, because I feel I'm on a slippery slope towards excluding everything!   \n",
-      "--Heron  05:16 18-06-2003\n",
-      "Let me put this another way.  I think the present article should be, as it mostly is, about the mathematics of large numbers.  Other large quantities, such as astronomical distances, already have a place on the orders of magnitude pages (1e10 m etc.)  Perhaps we should just link to them.   \n",
-      "--Heron  05:56 18-06-2003\n",
-      "Yes, you're quite right. Well, about most things. I could argue that physically distance is dimensionless but that would just be arrogant pedantry. The page title is \"large number\" not just \"large\", and the order of magnitude pages are pretty good for comparing distances. BTW did you see my reply for you on Wikipedia:Reference desk?   13:53 18 Jun 2003 (UTC)\n",
-      "--Tim Starling  09:53 18-06-2003\n",
-      "I agree with you about 1010.  I wouldn't call the number of bits on a hard disk particularly large, either.  It is certainly subjective.  My point was that measurements of distance etc. are different from pure numbers.  Measurements are, by definition, relative, whereas at least pure numbers are absolute.  Largeness is another thing.  Perhaps one definition would be \"a number considered as large at a particular time by a particular culture\".  For example, I seem to remember that the Old Testament uses the number 40 as a generic large number in several places (e.g. \"40 days and 40 nights\").   \n",
-      "--Heron  05:45 18-06-2003\n",
+      "https://en.wikipedia.org/w/index.php?title=user_talk:Jimfbleak\n",
       "\n",
       "\n",
       "\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:Creationism/Archive_6\n",
-      "Luckily my university has an institutional subscription to OED online. Here it is:\n",
-      "'''Creationism''' A system or theory of creation: ''spec.''    ''a.'' The theory that God immediately creates a soul for every human being born (opposed to traducianism);    ''b.'' The theory which attributes the origin of matter, the different species of animals and plants, etc., to `special creation' (opposed to evolutionism).\n",
-      "  \n",
-      "--Netesq  12:29 22-08-2003\n",
+      "https://en.wikipedia.org/w/index.php?title=talk:Homophobia/Archive_6\n",
       "\n",
       "\n",
       "\n"
      ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/sauna/conda-envs/zissou-env/lib/python3.7/site-packages/ipykernel_launcher.py:14: FutureWarning: speaker.name is deprecated and will be removed in a future release. Use speaker.id instead.\n"
-     ]
     }
    ],
    "source": [
@@ -443,29 +428,19 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "https://en.wikipedia.org/w/index.php?title=talk:Main_Page\n",
-      "age pump|Village pump]]. See talk:Wikipedia category schemes for general discussion of the category scheme on Wikipedia's Main Page.'''\n",
-      "'''See Wikipedia talk:Selected Articles on the Main Page for discussion of (and recommendations for) the Selected Articles on the Main Page. See below for more discussion of particular issues regarding the Main Page (e.g., whether to include a particular category on the page). Please add your additions at the bottom.'''\n",
-      "\n",
-      "Some older talk has been archived to\n",
-      "talk:Main Page/Archive 1\n",
-      "talk:Main Page/Archive 2\n",
-      "talk:Main Page/Archive 3\n",
-      "talk:Main Page/Archive 4\n",
-      "talk:Main Page/Archive 5\n",
-      "talk:Main Page/Archive 6\n",
-      "--Schneelocke  08:26 05-09-2003\n",
+      "https://en.wikipedia.org/w/index.php?title=user_talk:Daniel_C._Boyer/archive_1\n",
+      "Have you written this article? or do you have any idea about this article? (If you don't understand Korean, the title means \"unmarried girl backdoor\" or something.) Is it one of your work? \n",
+      "--217.0.84.251  15:36 07-04-2003\n",
+      "Yes; it should be The Tailgating Spinster (title of my book of poetry).  I apologise if my Korean is not good enough; perhaps you could provide a better translation of the title.  \n",
+      "--Daniel C. Boyer  10:47 09-04-2003\n",
+      "OK. I'll try to find a better translation. But due to my poor english, I can't understand the title. Does Tailgating mean ''chasing closely''? And does Spinster mean ''unmarried old woman''? \n",
+      "--Xaos~enwiki  23:02 09-04-2003\n",
+      "Yes; \"tailgating\" means (when one is driving) to follow too closely behind the car (or truck) in front of you.  A spinster is usually used to mean an ''unmaried old woman'' but it can mean an unmarried woman of any age (probably she would have to be old enough to be able to get married to qualify as a spinster).   19:43 Apr 10, 2003 (UTC)\n",
+      "--Daniel C. Boyer  15:43 10-04-2003\n",
       "\n",
       "\n",
       "\n"
      ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/sauna/conda-envs/zissou-env/lib/python3.7/site-packages/ipykernel_launcher.py:14: FutureWarning: speaker.name is deprecated and will be removed in a future release. Use speaker.id instead.\n"
-     ]
     }
    ],
    "source": [
@@ -543,7 +518,7 @@
     "            if (utterance_value.text != \" \"):\n",
     "                final_comment =  utterance_value.text\n",
     "                date_time_val = datetime.fromtimestamp(utterance_value.timestamp).strftime('%H:%M %d-%m-%Y')\n",
-    "                formatted_user_name = \"--\" + str(utterance_value.user.name) + \"  \" + str(date_time_val)\n",
+    "                formatted_user_name = \"--\" + str(utterance_value.speaker.id) + \"  \" + str(date_time_val)\n",
     "                \n",
     "        \n",
     "                final_timestamp = utterance_value.timestamp\n",
@@ -607,499 +582,25 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "https://en.wikipedia.org/w/index.php?title=talk:Book_of_Revelation/Archive_1\n",
-      "Final Comment\n",
-      "OK, I can go look up some info. I am a little unsure of which part is considered sweeping. I assume that we agree that this historical interpretation is common among non-Christians and secular Bible scholars. It will be easy for me to get references to the Catholic part of this claim; this view is what their new publications have taught, for well over 20 years. References will be forthcoming. As for the viewpoint of liberal protestants, this will take a bit more work! \n",
-      "--RK  21:39 24-04-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "OK, I can go look up some info. I am a little unsure of which part is considered sweeping. I assume that we agree that this historical interpretation is common among non-Christians and secular Bible scholars. It will be easy for me to get references to the Catholic part of this claim; this view is what their new publications have taught, for well over 20 years. References will be forthcoming. As for the viewpoint of liberal protestants, this will take a bit more work! \n",
-      "--RK  11:41 11-12-2002\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--RK  21:33 24-04-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "OK, I can go look up some info. I am a little unsure of which part is considered sweeping. I assume that we agree that this historical interpretation is common among non-Christians and secular Bible scholars. It will be easy for me to get references to the Catholic part of this claim; this view is what their new publications have taught, for well over 20 years. References will be forthcoming. As for the viewpoint of liberal protestants, this will take a bit more work! \n",
-      "--RK  21:39 24-04-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:Book_of_Revelation/Archive_1\n",
-      "Final Comment\n",
-      "RK, I believe you are confusing ''interpretation'' with ''criticism''. I remodeled the contentious paragraph, and included a link to an article on apocalyptic literature. If I understand what you mean by \"historical\", you are regarding the book as entirely concerned with events in the recent past as of the date of authorship, fused with vague predictions of Christ coming in fire and vengeance, etc.. If so, you are not discussing an interpretation of the book qua prophecy, but an understanding held by higher critics who treat the book as an example of apocalyptic literature. Please take it there, and feel free to go crazy! Don't forget the book of Enoch, and the many apocalyptic works of the Maccabean era. .\n",
-      "--RK  21:39 24-04-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "RK, I believe you are confusing ''interpretation'' with ''criticism''. I remodeled the contentious paragraph, and included a link to an article on apocalyptic literature. If I understand what you mean by \"historical\", you are regarding the book as entirely concerned with events in the recent past as of the date of authorship, fused with vague predictions of Christ coming in fire and vengeance, etc.. If so, you are not discussing an interpretation of the book qua prophecy, but an understanding held by higher critics who treat the book as an example of apocalyptic literature. Please take it there, and feel free to go crazy! Don't forget the book of Enoch, and the many apocalyptic works of the Maccabean era. .\n",
-      "--LenBudney  11:49 11-12-2002\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--RK  21:33 24-04-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "RK, I believe you are confusing ''interpretation'' with ''criticism''. I remodeled the contentious paragraph, and included a link to an article on apocalyptic literature. If I understand what you mean by \"historical\", you are regarding the book as entirely concerned with events in the recent past as of the date of authorship, fused with vague predictions of Christ coming in fire and vengeance, etc.. If so, you are not discussing an interpretation of the book qua prophecy, but an understanding held by higher critics who treat the book as an example of apocalyptic literature. Please take it there, and feel free to go crazy! Don't forget the book of Enoch, and the many apocalyptic works of the Maccabean era. .\n",
-      "--RK  21:39 24-04-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:Book_of_Revelation/Archive_1\n",
-      "Final Comment\n",
-      "Yes, I think we've achieved understanding! I think the distinction I make is useful for purposes of clarity, since the \"liberal Christians\" who agree with what you called the \"historical school\" are, in doing so, taking a controversial (to Christians) stance on the inspiration of scripture. They are rejecting the book's own claim to be foretelling the future, and agreeing with the criticism which classifies it as a pseudo-prophecy. It would be hard to include that as a \"school of interpretation\" without violating NPOV as to questions of authority, inspiration, etc.\n",
-      "--RK  21:39 24-04-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "Yes, I think we've achieved understanding! I think the distinction I make is useful for purposes of clarity, since the \"liberal Christians\" who agree with what you called the \"historical school\" are, in doing so, taking a controversial (to Christians) stance on the inspiration of scripture. They are rejecting the book's own claim to be foretelling the future, and agreeing with the criticism which classifies it as a pseudo-prophecy. It would be hard to include that as a \"school of interpretation\" without violating NPOV as to questions of authority, inspiration, etc.\n",
-      "--LenBudney  12:37 11-12-2002\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--RK  21:33 24-04-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "Yes, I think we've achieved understanding! I think the distinction I make is useful for purposes of clarity, since the \"liberal Christians\" who agree with what you called the \"historical school\" are, in doing so, taking a controversial (to Christians) stance on the inspiration of scripture. They are rejecting the book's own claim to be foretelling the future, and agreeing with the criticism which classifies it as a pseudo-prophecy. It would be hard to include that as a \"school of interpretation\" without violating NPOV as to questions of authority, inspiration, etc.\n",
-      "--RK  21:39 24-04-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      " King of Wikipedia \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      " King of Wikipedia \n",
-      "--Oliver Pereira  23:01 21-08-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      " King of Wikipedia \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      "I don't think you are. P  \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "I don't think you are. P  \n",
-      "--Oliver Pereira  23:01 21-08-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "I don't think you are. P  \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      "Ofcourse I am! Look at Wikipedia:King of Wikipedia\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "Ofcourse I am! Look at Wikipedia:King of Wikipedia\n",
-      "--BL~enwiki  23:02 21-08-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "Ofcourse I am! Look at Wikipedia:King of Wikipedia\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      "I will defeat you!  \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "I will defeat you!  \n",
-      "--Oliver Pereira  23:05 21-08-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "I will defeat you!  \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      "Hi BL, I'm curious why you re-instated the troll comment about jews ruling non-jews on the talk:Israel talk page. Going by the edits of that user on other pages, it wasn't a serious comment but something put on to deliberately provoke a reaction. Various pages linking to Israel or Jews have been targeted by a series of IPs in the 67 and 68 range, some provocatively hostile to Israel, some so sychophantically (may not be the right spelling but fuck it, I'm too knackered to care! -) ) pro-Israel they are unambiguously phoney. As you know, the Israel page and one or two others are like tinderboxes just waiting for someone to cast a match onto them. Whatever about rows over real comments, I thought it unwise to leave a crude piss-take that some people might believe was real and get angry over. We have had enough trouble on that page without phoney wind-up comments triggering off rows. -) \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "Hi BL, I'm curious why you re-instated the troll comment about jews ruling non-jews on the talk:Israel talk page. Going by the edits of that user on other pages, it wasn't a serious comment but something put on to deliberately provoke a reaction. Various pages linking to Israel or Jews have been targeted by a series of IPs in the 67 and 68 range, some provocatively hostile to Israel, some so sychophantically (may not be the right spelling but fuck it, I'm too knackered to care! -) ) pro-Israel they are unambiguously phoney. As you know, the Israel page and one or two others are like tinderboxes just waiting for someone to cast a match onto them. Whatever about rows over real comments, I thought it unwise to leave a crude piss-take that some people might believe was real and get angry over. We have had enough trouble on that page without phoney wind-up comments triggering off rows. -) \n",
-      "--Jtdirl  01:34 23-08-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "Hi BL, I'm curious why you re-instated the troll comment about jews ruling non-jews on the talk:Israel talk page. Going by the edits of that user on other pages, it wasn't a serious comment but something put on to deliberately provoke a reaction. Various pages linking to Israel or Jews have been targeted by a series of IPs in the 67 and 68 range, some provocatively hostile to Israel, some so sychophantically (may not be the right spelling but fuck it, I'm too knackered to care! -) ) pro-Israel they are unambiguously phoney. As you know, the Israel page and one or two others are like tinderboxes just waiting for someone to cast a match onto them. Whatever about rows over real comments, I thought it unwise to leave a crude piss-take that some people might believe was real and get angry over. We have had enough trouble on that page without phoney wind-up comments triggering off rows. -) \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      "By the way, would you stop yelling KEEEEP on the votes for deletion page?  It's very annoying \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "By the way, would you stop yelling KEEEEP on the votes for deletion page?  It's very annoying \n",
-      "--Robert Merkel  07:20 23-08-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "By the way, would you stop yelling KEEEEP on the votes for deletion page?  It's very annoying \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      "There's no need to go around shouting \"KEEEP IT!\" at people on Wikipedia:Votes for deletion. This being a text medium, people will \"hear\" you just as clearly if you simply say \"Keep it.\"\n",
-      "In fact, this being a text medium, people are ''more'' likely to pay attention to what you're trying to say if you demonstrate that you do know the correct use of lowercase letters, and the correct spelling of \"keep\".\n",
-      "—\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "There's no need to go around shouting \"KEEEP IT!\" at people on Wikipedia:Votes for deletion. This being a text medium, people will \"hear\" you just as clearly if you simply say \"Keep it.\"\n",
-      "In fact, this being a text medium, people are *more* likely to pay attention to what you're trying to say if you demonstrate that you do know the correct use of lowercase letters, and the correct spelling of \"keep\".\n",
-      "—\n",
-      "--Paul A  22:46 24-08-2003\n",
-      "\n",
-      "\n",
-      "modification\n",
-      "There's no need to go around shouting \"KEEEP IT!\" at people on Wikipedia:Votes for deletion. This being a text medium, people will \"hear\" you just as clearly if you simply say \"Keep it.\"\n",
-      "In fact, this being a text medium, people are ''more'' likely to pay attention to what you're trying to say if you demonstrate that you do know the correct use of lowercase letters, and the correct spelling of \"keep\".\n",
-      "—\n",
-      "--Paul A  22:48 24-08-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "There's no need to go around shouting \"KEEEP IT!\" at people on Wikipedia:Votes for deletion. This being a text medium, people will \"hear\" you just as clearly if you simply say \"Keep it.\"\n",
-      "In fact, this being a text medium, people are ''more'' likely to pay attention to what you're trying to say if you demonstrate that you do know the correct use of lowercase letters, and the correct spelling of \"keep\".\n",
-      "—\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      ")- 0717, Sep 8, 2003 (UTC)\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      ") - 0717, Sep 8, 2003 (UTC)\n",
-      "--Stevertigo  03:17 08-09-2003\n",
-      "\n",
-      "\n",
-      "modification\n",
-      ")- 0717, Sep 8, 2003 (UTC)\n",
-      "--Stevertigo  03:17 08-09-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      ")- 0717, Sep 8, 2003 (UTC)\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
+      "https://en.wikipedia.org/w/index.php?title=user_talk:Alex756/Archive\n",
       "Final Comment\n",
-      "English spellings should not be changed to American without good reason. Why did you change Kilometre to Kilometer in Km/h? The page is located at Kilometre anyway, so you are now causing a redirect to occur. See Wikipedia:Manual of Style. It is generally accepted that the version used by the original author is kept.  23:04, Sep 17, 2003 (UTC)\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
+      " Points of order \n",
+      "--142.177.103.185  19:51 13-10-2003\n",
       "\n",
       "\n",
       "original\n",
-      "English spellings should not be changed to American without good reason. Why did you change Kilometre to Kilometer in Km/h? The page is located at Kilometre anyway, so you are now causing a redirect to occur. See Wikipedia:Manual of Style. It is generally accepted that the version used by the original author is kept.  23:04, Sep 17, 2003 (UTC)\n",
-      "--Angela  19:04 17-09-2003\n",
-      "\n",
-      "\n",
-      "modification\n",
-      "English spellings should not be changed to American without good reason. Why did you change Kilometre to Kilometer in Km/h? The page is located at Kilometre anyway, so you are now causing a redirect to occur. See Wikipedia:Manual of Style. It is generally accepted that the version used by the original author is kept.  23:04, Sep 17, 2003 (UTC)\n",
-      "--MartinHarper  20:46 20-09-2003\n",
+      " Points of order \n",
+      "--142.177.78.145  19:38 13-10-2003\n",
       "\n",
       "\n",
       "deletion\n",
       "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
+      "--MartinHarper  19:40 13-10-2003\n",
       "\n",
       "\n",
       "restoration\n",
-      "English spellings should not be changed to American without good reason. Why did you change Kilometre to Kilometer in Km/h? The page is located at Kilometre anyway, so you are now causing a redirect to occur. See Wikipedia:Manual of Style. It is generally accepted that the version used by the original author is kept.  23:04, Sep 17, 2003 (UTC)\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      "Ok, you might find American and British English Differences and http://www.onelook.com/ useful.  23:28, Sep 17, 2003 (UTC)\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "Ok, you might find American and British English Differences and http://www.onelook.com/ useful.  23:28, Sep 17, 2003 (UTC)\n",
-      "--Angela  19:28 17-09-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "Ok, you might find American and British English Differences and http://www.onelook.com/ useful.  23:28, Sep 17, 2003 (UTC)\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      "Could you read and respond to Talk:The_Chronicles_of_George?  12:40, 17 Sep 2003 (UTC)\n",
-      " Hello? Is this thing on? *tap* *tap* *tap*.  00:46, 21 Sep 2003 (UTC)\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "Could you read and respond to Talk:The_Chronicles_of_George?  12:40, 17 Sep 2003 (UTC)\n",
-      " Hello? Is this thing on? *tap* *tap* *tap*.  00:46, 21 Sep 2003 (UTC)\n",
-      "--MartinHarper  20:46 20-09-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "Could you read and respond to Talk:The_Chronicles_of_George?  12:40, 17 Sep 2003 (UTC)\n",
-      " Hello? Is this thing on? *tap* *tap* *tap*.  00:46, 21 Sep 2003 (UTC)\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      " Uh, I dropped it earlier... \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      " Uh, I dropped it earlier... \n",
-      "--Pizza Puzzle  20:56 20-09-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      " Uh, I dropped it earlier... \n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      "How is stating that a consensus is not required an \"impractical\" statement?  17:57, 24 Sep 2003 (UTC)\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "How is stating that a consensus is not required an \"impractical\" statement?  17:57, 24 Sep 2003 (UTC)\n",
-      "--Angela  13:57 24-09-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--142.177.74.112  13:06 25-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "How is stating that a consensus is not required an \"impractical\" statement?  17:57, 24 Sep 2003 (UTC)\n",
-      "--BL~enwiki  13:28 25-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:BL~enwiki\n",
-      "Final Comment\n",
-      "I enjoyed reading your astute comments on the privatization page. A while ago, I added content to the privatization page, specifically the theory behind it. While I agree that it's generally valid theoretically, your points are often correct in practice.\n",
-      "Since it seems that you're also interested in economic policy, you might want to take a look at some content that I added a while ago to the History of post-communist Russia article. It's the best example on Wikipedia, of which I'm aware, of an in depth look at privatization in practice. Specifically, you might be interested in the sections on the three stages of privatization in Russia and the next section on the so-called \"virtual economy\" (a term coined by economists Clifford Gaddy and Barry Ickes in reference to post-Communist Russia). Since it's a long article, you'd be able to find these sections by clicking on the link in the pop up table of contents box at the top; the sections of privatization are under the broader heading of \"democratization and its setbacks.\" (Just to make a brief note about the structure of the article, the content doesn't really separate sections on economic restructuring and democratization, since they're so intertwined in a country remaking both its economic and political institutions.)\n",
-      "The sections that I'm recommending bring up all the sharp insights that you made (i.e. that design is more important than the mere transfer of ownership). Here, I'll just summarize the points made in the Russia article. State monopolies were rarely restructured before privatization. Thus, there was little competition over price and quality for consumer demand. In turn, there were few incentives to invest capital to salvage inefficient value-losing enterprises. Thus, efficiency (in terms of minimizing costs per unit of output) rarely improved. Instead of channeling investment into privatized enterprises, asset stripping (facilitated by capital market liberalization) was the common result. Moreover, despite sweeping openings, capital markets (i.e. the mechanisms to channel private savings into Russian companies) remain week.\n",
-      "It would be great if your interest in the articles on post-Communist Russia were aroused since I cannot find anyone interested in this subject. This is baffling since it is such a contentious topic. In academic literature (and especially within Russia), reform strategies, the sequencing of reform, and the pace of reform in post-Communist Russia remain contentious topics, argued often with great personal bitterness. After all, many prominent former Soviet specialists in the West were very active in the design of new economic and political institutions in Russia. Subject to harsh retrospective criticism, many economists at the US Treasury Department, IMF, World Bank, and top US universities have become very defensive. It's still a heated subject in the top journals, academic literature, and major periodicals on Russia and economics.\n",
-      "Anyway, sorry if my comments were a bit on the lengthy side. Don't feel compelled to redirect your attention to post-Communist Russia if you're uninterested. It's only my guess that you would be from your insightful comments.  06:03, 29 Sep 2003 (UTC)\n",
-      "BTW, since you are frequent contributor to Palestinian-related articles, I'm sure that the loss of the great scholar Edward Said isn't news to you. I don't know your feelings about him, but I think that his passing couldn't have come at a worse time. I'd argue that the popular writings on the Middle East in the US, exemplified by Daniel Pipes, are simply bigoted and hateful. It's sad to see such an effective counterweight to their venom gone.   06:03, 29 Sep 2003 (UTC)\n",
-      "--172  02:36 29-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "I enjoyed reading your astute comments on the privatization page. A while ago, I added content to the privatization page, specifically the theory behind it. While I agree that it's generally valid theoretically, your points are often correct in practice.\n",
-      "Since it seems that you're also interested in economic policy, you might want to take a look at some content that I added a while ago to the History of post-communist Russia article. It's the best example on Wikipedia, of which I'm aware, of an in depth look at privatization in practice. Specifically, you might be interested in the sections on the three stages of privatization in Russia and the next section on the so-called \"virtual economy\" (a term coined by economists Clifford Gaddy and Barry Ickes in reference to post-Communist Russia). Since it's a long article, you'd be able to find these sections by clicking on the link in the pop up table of contents box at the top; the sections of privatization are under the broader heading of \"democratization and its setbacks.\" (Just to make a brief note about the structure of the article, the content doesn't really separate sections on economic restructuring and democratization, since they're so intertwined in a country remaking both its economic and political institutions.)\n",
-      "The sections that I'm recommending bring up all the sharp insights that you made (that design is more important than the mere transfer of ownership). Here, I'll just summarize the points made in the Russia article. State monopolies were rarely restructured before privatization. Thus, there was little competition over price and quality for consumer demand. In turn, there were few incentives to invest capital to salvage inefficient value-losing enterprises. Thus, efficiency (minimizing costs per unit of output) rarely improved. Instead of channeling investment into privatized enterprises, asset stripping (facilitated by capital market liberalization) was the common result. Moreover, despite sweeping openings, capital markets (the mechanisms to channel private savings into Russian companies) remain week.\n",
-      "It would be great if your interest in the articles on post-Communist Russia were aroused since I cannot find anyone interested in this subject. This is baffling since it is such a contentious topic. In academic literature (and especially within Russia), reform strategies, the sequencing of reform, and the pace of reform in post-Communist Russia remain contentious topics, argued often with great personal bitterness. After all, many prominent former Soviet specialists in the West were very active in the design of new economic and political institutions in Russia. Subject to harsh retrospective criticism, many economists at the US Treasury Department, IMF, World Bank, and top US universities have become very defensive. It's still a heated subject in the top journals, academic literature, and major periodicals on Russia and economics.\n",
-      "Anyway, sorry if my comments were a bit on the lengthy side. Don't feel compelled to redirect your attention to post-Communist Russia if you're uninterested. It's only my guess that you would be from your insightful comments.  06:03, 29 Sep 2003 (UTC)\n",
-      "BTW, since you are frequently contributor to Palestinian-related articles, I'm sure that the loss of the great scholar Edward Said isn't news to you. I don't know your feelings about him, but I think that his passing couldn't have come at a worse time. I'd argue that the popular writings on the Middle East in the US, exemplified by Daniel Pipes, are simply bigoted and hateful. It's sad to see such an effective counterweight to their venom gone.   06:03, 29 Sep 2003 (UTC)\n",
-      "--172  02:03 29-09-2003\n",
-      "\n",
-      "\n",
-      "modification\n",
-      "I enjoyed reading your astute comments on the privatization page. A while ago, I added content to the privatization page, specifically the theory behind it. While I agree that it's generally valid theoretically, your points are often correct in practice.\n",
-      "Since it seems that you're also interested in economic policy, you might want to take a look at some content that I added a while ago to the History of post-communist Russia article. It's the best example on Wikipedia, of which I'm aware, of an in depth look at privatization in practice. Specifically, you might be interested in the sections on the three stages of privatization in Russia and the next section on the so-called \"virtual economy\" (a term coined by economists Clifford Gaddy and Barry Ickes in reference to post-Communist Russia). Since it's a long article, you'd be able to find these sections by clicking on the link in the pop up table of contents box at the top; the sections of privatization are under the broader heading of \"democratization and its setbacks.\" (Just to make a brief note about the structure of the article, the content doesn't really separate sections on economic restructuring and democratization, since they're so intertwined in a country remaking both its economic and political institutions.)\n",
-      "The sections that I'm recommending bring up all the sharp insights that you made (that design is more important than the mere transfer of ownership). Here, I'll just summarize the points made in the Russia article. State monopolies were rarely restructured before privatization. Thus, there was little competition over price and quality for consumer demand. In turn, there were few incentives to invest capital to salvage inefficient value-losing enterprises. Thus, efficiency (minimizing costs per unit of output) rarely improved. Instead of channeling investment into privatized enterprises, asset stripping (facilitated by capital market liberalization) was the common result. Moreover, despite sweeping openings, capital markets (the mechanisms to channel private savings into Russian companies) remain week.\n",
-      "It would be great if your interest in the articles on post-Communist Russia were aroused since I cannot find anyone interested in this subject. This is baffling since it is such a contentious topic. In academic literature (and especially within Russia), reform strategies, the sequencing of reform, and the pace of reform in post-Communist Russia remain contentious topics, argued often with great personal bitterness. After all, many prominent former Soviet specialists in the West were very active in the design of new economic and political institutions in Russia. Subject to harsh retrospective criticism, many economists at the US Treasury Department, IMF, World Bank, and top US universities have become very defensive. It's still a heated subject in the top journals, academic literature, and major periodicals on Russia and economics.\n",
-      "Anyway, sorry if my comments were a bit on the lengthy side. Don't feel compelled to redirect your attention to post-Communist Russia if you're uninterested. It's only my guess that you would be from your insightful comments.  06:03, 29 Sep 2003 (UTC)\n",
-      "BTW, since you are frequent contributor to Palestinian-related articles, I'm sure that the loss of the great scholar Edward Said isn't news to you. I don't know your feelings about him, but I think that his passing couldn't have come at a worse time. I'd argue that the popular writings on the Middle East in the US, exemplified by Daniel Pipes, are simply bigoted and hateful. It's sad to see such an effective counterweight to their venom gone.   06:03, 29 Sep 2003 (UTC)\n",
-      "--172  02:07 29-09-2003\n",
-      "\n",
-      "\n",
-      "modification\n",
-      "I enjoyed reading your astute comments on the privatization page. A while ago, I added content to the privatization page, specifically the theory behind it. While I agree that it's generally valid theoretically, your points are often correct in practice.\n",
-      "Since it seems that you're also interested in economic policy, you might want to take a look at some content that I added a while ago to the History of post-communist Russia article. It's the best example on Wikipedia, of which I'm aware, of an in depth look at privatization in practice. Specifically, you might be interested in the sections on the three stages of privatization in Russia and the next section on the so-called \"virtual economy\" (a term coined by economists Clifford Gaddy and Barry Ickes in reference to post-Communist Russia). Since it's a long article, you'd be able to find these sections by clicking on the link in the pop up table of contents box at the top; the sections of privatization are under the broader heading of \"democratization and its setbacks.\" (Just to make a brief note about the structure of the article, the content doesn't really separate sections on economic restructuring and democratization, since they're so intertwined in a country remaking both its economic and political institutions.)\n",
-      "The sections that I'm recommending bring up all the sharp insights that you made (i.e. that design is more important than the mere transfer of ownership). Here, I'll just summarize the points made in the Russia article. State monopolies were rarely restructured before privatization. Thus, there was little competition over price and quality for consumer demand. In turn, there were few incentives to invest capital to salvage inefficient value-losing enterprises. Thus, efficiency (in terms of minimizing costs per unit of output) rarely improved. Instead of channeling investment into privatized enterprises, asset stripping (facilitated by capital market liberalization) was the common result. Moreover, despite sweeping openings, capital markets (i.e. the mechanisms to channel private savings into Russian companies) remain week.\n",
-      "It would be great if your interest in the articles on post-Communist Russia were aroused since I cannot find anyone interested in this subject. This is baffling since it is such a contentious topic. In academic literature (and especially within Russia), reform strategies, the sequencing of reform, and the pace of reform in post-Communist Russia remain contentious topics, argued often with great personal bitterness. After all, many prominent former Soviet specialists in the West were very active in the design of new economic and political institutions in Russia. Subject to harsh retrospective criticism, many economists at the US Treasury Department, IMF, World Bank, and top US universities have become very defensive. It's still a heated subject in the top journals, academic literature, and major periodicals on Russia and economics.\n",
-      "Anyway, sorry if my comments were a bit on the lengthy side. Don't feel compelled to redirect your attention to post-Communist Russia if you're uninterested. It's only my guess that you would be from your insightful comments.  06:03, 29 Sep 2003 (UTC)\n",
-      "BTW, since you are frequent contributor to Palestinian-related articles, I'm sure that the loss of the great scholar Edward Said isn't news to you. I don't know your feelings about him, but I think that his passing couldn't have come at a worse time. I'd argue that the popular writings on the Middle East in the US, exemplified by Daniel Pipes, are simply bigoted and hateful. It's sad to see such an effective counterweight to their venom gone.   06:03, 29 Sep 2003 (UTC)\n",
-      "--172  02:36 29-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=user_talk:Angela/Archive1\n",
-      "Final Comment\n",
-      "Industrial Waste\n",
-      "--Angela  19:10 10-12-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "Industrial Waste\n",
-      "--Ed Poor  14:30 09-12-2003\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--Angela  15:05 09-12-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "Industrial Waste\n",
-      "--Angela  19:10 10-12-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:List_of_one-hit_wonders_on_the_UK_Singles_Chart\n",
-      "Final Comment\n",
-      "Just wondering on what grounds some of these songs are termed one hit wonders... I mean I just removed \"A-Ha - Take On Me\" because A-Ha were one of the bigger acts of the 80s, with a string of top 10 hits. Kajagoogoo, while being best known for Too Shy, had two other Top 10 hits, and a further top 20 hit. Let alone the top 40.\n",
-      "The Guinness Book of Hit Singles would tell us that a one hit wonder has to get to number one. I disagree with that, but would insist that a one hit wonder really has to have had only ONE HIT. Whether that's a top 40 hit or a top 75 hit is open to debate perhaps... But a LOT of these acts had more than one hit. -\n",
-      "--Mintguy  11:11 12-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "Just wondering on what grounds some of these songs are termed one hit wonders... I mean I just removed \"A-Ha - Take On Me\" because A-Ha were one of the bigger acts of the 80s, with a string of top 10 hits. Kajagoogoo, while being best known for Too Shy, had two other Top 10 hits, and a further top 20 hit. Let alone the top 40.\n",
-      "The Guinness Book of Hit Singles would tell us that a one hit wonder has to get to number one. I disagree with that, but would insist that a one hit wonder really has to have had only ONE HIT. Whether that's a top 40 hit or a top 75 hit is open to debate perhaps... But a LOT of these acts had more than one hit. -\n",
-      "--Nommonomanac  21:30 03-12-2002\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--213.122.51.46  11:06 12-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "Just wondering on what grounds some of these songs are termed one hit wonders... I mean I just removed \"A-Ha - Take On Me\" because A-Ha were one of the bigger acts of the 80s, with a string of top 10 hits. Kajagoogoo, while being best known for Too Shy, had two other Top 10 hits, and a further top 20 hit. Let alone the top 40.\n",
-      "The Guinness Book of Hit Singles would tell us that a one hit wonder has to get to number one. I disagree with that, but would insist that a one hit wonder really has to have had only ONE HIT. Whether that's a top 40 hit or a top 75 hit is open to debate perhaps... But a LOT of these acts had more than one hit. -\n",
-      "--Mintguy  11:11 12-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:List_of_one-hit_wonders_on_the_UK_Singles_Chart\n",
-      "Final Comment\n",
-      "I think if a band had a top 10 hit and had a few bubling under the top ten it's kinda borderline. What do you think?  02:55 Dec 4, 2002 (UTC)\n",
-      "--Mintguy  11:11 12-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      "I think if a band had a top 10 hit and had a few bubling under the top ten it's kinda borderline. What do you think?  02:55 Dec 4, 2002 (UTC)\n",
-      "--Mintguy  21:55 03-12-2002\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--213.122.51.46  11:06 12-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      "I think if a band had a top 10 hit and had a few bubling under the top ten it's kinda borderline. What do you think?  02:55 Dec 4, 2002 (UTC)\n",
-      "--Mintguy  11:11 12-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:List_of_one-hit_wonders_on_the_UK_Singles_Chart\n",
-      "Final Comment\n",
-      " Well... the way I see it, I'd say that a seperate top 40 hit would negate a top 10 hit's OHW status. I mean, if a band gets one record in the top ten and no others in the top 40, that seems to me to work out as a OHW. But a top ten and another in the top 40 doesn't... It means we don't have to worry about a massive amount of records - just a ''lot'' of records. More than one record in the top 40 doesn't seem like a OHW to me. -\n",
-      "--Mintguy  11:11 12-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      " Well... the way I see it, I'd say that a seperate top 40 hit would negate a top 10 hit's OHW status. I mean, if a band gets one record in the top ten and no others in the top 40, that seems to me to work out as a OHW. But a top ten and another in the top 40 doesn't... It means we don't have to worry about a massive amount of records - just a ''lot'' of records. More than one record in the top 40 doesn't seem like a OHW to me. -\n",
-      "--Nommonomanac  22:02 03-12-2002\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--213.122.51.46  11:06 12-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      " Well... the way I see it, I'd say that a seperate top 40 hit would negate a top 10 hit's OHW status. I mean, if a band gets one record in the top ten and no others in the top 40, that seems to me to work out as a OHW. But a top ten and another in the top 40 doesn't... It means we don't have to worry about a massive amount of records - just a ''lot'' of records. More than one record in the top 40 doesn't seem like a OHW to me. -\n",
-      "--Mintguy  11:11 12-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:List_of_one-hit_wonders_on_the_UK_Singles_Chart\n",
-      "Final Comment\n",
-      " Hmmm... It's difficult Billy Ray Curtis got another song (\"\"Could've been me\"\") to 24, but I doubt if anyone (but a fan) could remember it. It would be a shame to remove him. Channel 4 had a top 10 one hit wonder thing a while ago. I wonder what criteria they used.\n",
-      "--Mintguy  11:11 12-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      " Hmmm... It's difficult Billy Ray Curtis got another song (\"\"Could've been me\"\") to 24, but I doubt if anyone (but a fan) could remember it. It would be a shame to remove him. Channel 4 had a top 10 one hit wonder thing a while ago. I wonder what criteria they used.\n",
-      "--Mintguy  22:10 03-12-2002\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--213.122.51.46  11:06 12-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      " Hmmm... It's difficult Billy Ray Curtis got another song (\"\"Could've been me\"\") to 24, but I doubt if anyone (but a fan) could remember it. It would be a shame to remove him. Channel 4 had a top 10 one hit wonder thing a while ago. I wonder what criteria they used.\n",
-      "--Mintguy  11:11 12-09-2003\n",
-      "https://en.wikipedia.org/w/index.php?title=talk:List_of_one-hit_wonders_on_the_UK_Singles_Chart\n",
-      "Final Comment\n",
-      " Weren't they all number ones? I seem to remember a second Billy Ray Cyrus record coming out. I remember a small amount of associated pain. Though I don't remember the song. Reneé and Renato were in that C4 thing... They had a number 1 and a number 48, so that would fit my criteria. Which seems right. -\n",
-      "--Mintguy  11:11 12-09-2003\n",
-      "\n",
-      "\n",
-      "original\n",
-      " Weren't they all number ones? I seem to remember a second Billy Ray Cyrus record coming out. I remember a small amount of associated pain. Though I don't remember the song. Reneé and Renato were in that C4 thing... They had a number 1 and a number 48, so that would fit my criteria. Which seems right. -\n",
-      "--Nommonomanac  08:28 05-12-2002\n",
-      "\n",
-      "\n",
-      "deletion\n",
-      "\n",
-      "--213.122.51.46  11:06 12-09-2003\n",
-      "\n",
-      "\n",
-      "restoration\n",
-      " Weren't they all number ones? I seem to remember a second Billy Ray Cyrus record coming out. I remember a small amount of associated pain. Though I don't remember the song. Reneé and Renato were in that C4 thing... They had a number 1 and a number 48, so that would fit my criteria. Which seems right. -\n",
-      "--Mintguy  11:11 12-09-2003\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/sauna/conda-envs/zissou-env/lib/python3.7/site-packages/ipykernel_launcher.py:12: FutureWarning: speaker.name is deprecated and will be removed in a future release. Use speaker.id instead.\n"
+      " Points of order \n",
+      "--142.177.103.185  19:51 13-10-2003\n"
      ]
     }
    ],
@@ -1139,7 +640,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.7"
+   "version": "3.9.0"
   }
  },
  "nbformat": 4,
diff --git a/examples/dataset-examples/wikiconv/corpus_deletion_demo.ipynb b/examples/dataset-examples/wikiconv/corpus_deletion_demo.ipynb
index 49a552da..70919056 100644
--- a/examples/dataset-examples/wikiconv/corpus_deletion_demo.ipynb
+++ b/examples/dataset-examples/wikiconv/corpus_deletion_demo.ipynb
@@ -29,7 +29,7 @@
    "source": [
     "#import relevant modules\n",
     "from datetime import datetime, timedelta\n",
-    "from convokit import Corpus, User, Utterance, Conversation, download"
+    "from convokit import Corpus, Utterance, Conversation, download"
    ]
   },
   {
@@ -41,7 +41,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Dataset already exists at /home/jonathan/.convokit/downloads/wikiconv-2003\n"
+      "Dataset already exists at /Users/seanzhangkx/.convokit/downloads/wikiconv-2003\n"
      ]
     }
    ],
@@ -113,7 +113,7 @@
     {
      "data": {
       "text/plain": [
-       "Utterance({'id': '5021479.2081.2077', 'user': User([('name', 'Jay')]), 'root': '5021479.1277.1272', 'reply_to': '5021479.1277.1272', 'timestamp': 1070614595.0, 'text': \"You're right about separating the sandwich of war names and MiG names. Each plane should be sorted chronologically and have its own sentence detailing its importance. \", 'meta': {'is_section_header': True, 'indentation': '2', 'toxicity': 0.1219038, 'sever_toxicity': 0.06112729, 'ancestor_id': '5021479.2081.2077', 'rev_id': '5021479', 'parent_id': None, 'original': None, 'modification': [], 'deletion': [], 'restoration': []}})"
+       "Utterance({'obj_type': 'utterance', 'vectors': [], 'speaker_': Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fbe80d0bfd0>, 'id': 'Jay', 'meta': ConvoKitMeta({'user_id': '14784'})}), 'owner': <convokit.model.corpus.Corpus object at 0x7fbe80d0bfd0>, 'id': '5021479.2081.2077', 'meta': ConvoKitMeta({'is_section_header': True, 'indentation': '2', 'toxicity': 0.1219038, 'sever_toxicity': 0.06112729, 'ancestor_id': '5021479.2081.2077', 'rev_id': '5021479', 'parent_id': None, 'original': None, 'modification': [], 'deletion': [], 'restoration': []})})"
       ]
      },
      "execution_count": 5,
@@ -145,9 +145,9 @@
     "    count_sever_toxic = 0\n",
     "    \n",
     "    for deletion_utt in list_of_deletion_utterances:\n",
-    "        toxicity_val = deletion_utt.meta['toxicity']\n",
-    "        sever_toxicity_val = deletion_utt.meta['sever_toxicity']\n",
-    "        timestamp_value = deletion_utt.timestamp\n",
+    "        toxicity_val = deletion_utt[\"meta\"]['toxicity']\n",
+    "        sever_toxicity_val = deletion_utt[\"meta\"]['sever_toxicity']\n",
+    "        timestamp_value = deletion_utt[\"timestamp\"]\n",
     "        deletion_datetime_val = datetime.fromtimestamp(timestamp_value)\n",
     "        \n",
     "        #delta_value is the time delta between when the deletion utt happened and the original utt's posting \n",
@@ -166,8 +166,7 @@
     "                    count_sever_toxic +=1 \n",
     "    \n",
     "    #Return in  tuple  form the number of each type of affected comment\n",
-    "    return (count_normal, count_toxic, count_sever_toxic)\n",
-    "                    "
+    "    return (count_normal, count_toxic, count_sever_toxic)"
    ]
   },
   {
@@ -224,7 +223,7 @@
     "        #Find the time that the original utterance is posted\n",
     "        original_utterance = utterance_value.meta['original']\n",
     "        if (original_utterance is not None):\n",
-    "            original_time = original_utterance.timestamp\n",
+    "            original_time = original_utterance['timestamp']\n",
     "            original_date_time = datetime.fromtimestamp(original_time)\n",
     "        else:\n",
     "            original_date_time =  datetime.fromtimestamp(utterance_value.timestamp)\n",
@@ -303,6 +302,7 @@
     " total_normal, total_toxic, total_sever) = get_deletion_counts(individual_utterance_list, timedelta_value)\n",
     "print_statistics(count_normal_deleted, count_toxic_deleted, count_sever_deleted,\n",
     "                 total_normal,  total_toxic, total_sever)\n",
+    "\n",
     "\n"
    ]
   },
@@ -414,7 +414,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.2"
+   "version": "3.9.0"
   }
  },
  "nbformat": 4,
diff --git a/examples/hyperconvo/hyperconvo_demo.ipynb b/examples/hyperconvo/hyperconvo_demo.ipynb
index d46ef45d..1e461993 100644
--- a/examples/hyperconvo/hyperconvo_demo.ipynb
+++ b/examples/hyperconvo/hyperconvo_demo.ipynb
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -24,7 +24,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -43,14 +43,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Dataset already exists at /Users/calebchiam/Documents/GitHub/ConvoKit/convokit/tensors/reddit-corpus-small\n"
+      "Dataset already exists at /Users/seanzhangkx/.convokit/downloads/reddit-corpus-small\n"
      ]
     }
    ],
@@ -60,19 +60,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'subreddit': 'reddit-corpus-small',\n",
-       " 'num_posts': 8286,\n",
-       " 'num_comments': 288846,\n",
-       " 'num_user': 119889}"
+       "ConvoKitMeta({'subreddit': 'reddit-corpus-small', 'num_posts': 8286, 'num_comments': 288846, 'num_user': 119889})"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -83,7 +80,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -118,7 +115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -127,7 +124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -136,7 +133,7 @@
        "10000"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -147,11 +144,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
-    "threads_corpus = corpus.reindex_conversations(new_convo_roots=top_level_utterance_ids, \n",
+    "threads_corpus = corpus.reindex_conversations(source_corpus=corpus,\n",
+    "                                              new_convo_roots=top_level_utterance_ids, \n",
     "                                              preserve_convo_meta=True,\n",
     "                                              preserve_corpus_meta=False)"
    ]
@@ -165,27 +163,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Utterance({'obj_type': 'utterance', '_owner': <convokit.model.corpus.Corpus object at 0x122dbf490>, 'meta': {'score': 4091, 'top_level_comment': None, 'retrieved_on': 1540057333, 'gilded': 0, 'gildings': {'gid_1': 0, 'gid_2': 0, 'gid_3': 0}, 'subreddit': 'tifu', 'stickied': False, 'permalink': '/r/tifu/comments/9bzh9g/tifu_by_masturbating_with_my_dads_penis/', 'author_flair_text': ''}, '_id': '9bzh9g', 'vectors': [], 'speaker': Speaker({'obj_type': 'speaker', '_owner': <convokit.model.corpus.Corpus object at 0x122dbf490>, 'meta': {'num_posts': 1, 'num_comments': 0}, '_id': 'gerbalt', 'vectors': []}), 'conversation_id': '9bzh9g', '_root': '9bzh9g', 'reply_to': None, 'timestamp': 1535767318, 'text': '[removed]'})"
+       "Utterance({'obj_type': 'utterance', 'vectors': [], 'speaker_': Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7facb8595cd0>, 'id': 'Prestonurvagi', 'meta': ConvoKitMeta({'num_posts': 0, 'num_comments': 1})}), 'owner': <convokit.model.corpus.Corpus object at 0x7facb8595cd0>, 'id': 'e63uqhy', 'meta': ConvoKitMeta({'score': 1, 'top_level_comment': 'e63uqhy', 'retrieved_on': 1539133743, 'gilded': 0, 'gildings': {'gid_1': 0, 'gid_2': 0, 'gid_3': 0}, 'subreddit': 'sex', 'stickied': False, 'permalink': '/r/sex/comments/9gfh93/first_day_of_my_menstrual_cycle_and_im_wanting/e63uqhy/', 'author_flair_text': ''})})"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "corpus.get_utterance('9bzh9g')"
+    "corpus.random_utterance()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -204,7 +202,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -238,7 +236,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -247,7 +245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -308,7 +306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -338,7 +336,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -382,16 +380,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<convokit.model.corpus.Corpus at 0x13e91d2d0>"
+       "<convokit.model.corpus.Corpus at 0x7facb8595cd0>"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -412,7 +410,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -421,7 +419,7 @@
        "{'hyperconvo'}"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -432,14 +430,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "e6p7yrp\n"
+      "e5hm9mp\n"
      ]
     }
    ],
@@ -451,17 +449,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
        "<1x140 sparse matrix of type '<class 'numpy.float64'>'\n",
-       "\twith 130 stored elements in Compressed Sparse Row format>"
+       "\twith 132 stored elements in Compressed Sparse Row format>"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -472,7 +470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -496,710 +494,707 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>2nd-argmax[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-argmax[indegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-argmax[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-argmax[indegree over C-&gt;c responses]</th>\n",
-       "      <th>2nd-argmax[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>max[indegree over c-&gt;c responses]</th>\n",
+       "      <th>argmax[indegree over c-&gt;c responses]</th>\n",
+       "      <th>norm.max[indegree over c-&gt;c responses]</th>\n",
+       "      <th>2nd-largest[indegree over c-&gt;c responses]</th>\n",
        "      <th>2nd-argmax[indegree over c-&gt;c responses]</th>\n",
-       "      <th>2nd-argmax[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-argmax[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-argmax[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-argmax[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>2nd-largest / max[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-largest / max[indegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-largest / max[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-largest / max[indegree over C-&gt;c responses]</th>\n",
-       "      <th>2nd-largest / max[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over c-&gt;c responses]</th>\n",
+       "      <th>mean[indegree over c-&gt;c responses]</th>\n",
+       "      <th>mean-nonzero[indegree over c-&gt;c responses]</th>\n",
+       "      <th>prop-nonzero[indegree over c-&gt;c responses]</th>\n",
+       "      <th>prop-multiple[indegree over c-&gt;c responses]</th>\n",
+       "      <th>entropy[indegree over c-&gt;c responses]</th>\n",
        "      <th>2nd-largest / max[indegree over c-&gt;c responses]</th>\n",
-       "      <th>2nd-largest / max[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-largest / max[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-largest / max[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-largest / max[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>2nd-largest[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-largest[indegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-largest[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-largest[indegree over C-&gt;c responses]</th>\n",
-       "      <th>2nd-largest[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-largest[indegree over c-&gt;c responses]</th>\n",
-       "      <th>2nd-largest[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-largest[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-largest[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-largest[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>argmax[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>argmax[indegree over C-&gt;C responses]</th>\n",
-       "      <th>argmax[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>argmax[indegree over C-&gt;c responses]</th>\n",
-       "      <th>argmax[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>argmax[indegree over c-&gt;c responses]</th>\n",
-       "      <th>argmax[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>argmax[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>argmax[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>max[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>max[indegree over C-&gt;c responses]</th>\n",
        "      <th>argmax[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>count[dyadic interaction motif over mid-thread]</th>\n",
-       "      <th>count[dyadic interaction motif]</th>\n",
-       "      <th>count[external reciprocity motif over mid-thread]</th>\n",
-       "      <th>count[external reciprocity motif]</th>\n",
-       "      <th>count[incoming triads over mid-thread]</th>\n",
-       "      <th>count[incoming triads]</th>\n",
-       "      <th>count[outgoing triads over mid-thread]</th>\n",
-       "      <th>count[outgoing triads]</th>\n",
-       "      <th>count[reciprocity motif over mid-thread]</th>\n",
-       "      <th>count[reciprocity motif]</th>\n",
-       "      <th>entropy[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>entropy[indegree over C-&gt;C responses]</th>\n",
-       "      <th>entropy[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>argmax[indegree over C-&gt;c responses]</th>\n",
+       "      <th>norm.max[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>norm.max[indegree over C-&gt;c responses]</th>\n",
+       "      <th>2nd-largest[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>2nd-largest[indegree over C-&gt;c responses]</th>\n",
+       "      <th>2nd-argmax[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>2nd-argmax[indegree over C-&gt;c responses]</th>\n",
+       "      <th>norm.2nd-largest[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over C-&gt;c responses]</th>\n",
+       "      <th>mean[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>mean[indegree over C-&gt;c responses]</th>\n",
+       "      <th>mean-nonzero[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>mean-nonzero[indegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-nonzero[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-nonzero[indegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-multiple[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-multiple[indegree over C-&gt;c responses]</th>\n",
+       "      <th>entropy[outdegree over C-&gt;c responses]</th>\n",
        "      <th>entropy[indegree over C-&gt;c responses]</th>\n",
-       "      <th>entropy[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>entropy[indegree over c-&gt;c responses]</th>\n",
-       "      <th>entropy[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>2nd-largest / max[indegree over C-&gt;c responses]</th>\n",
+       "      <th>max[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>max[indegree over C-&gt;C responses]</th>\n",
+       "      <th>argmax[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>argmax[indegree over C-&gt;C responses]</th>\n",
+       "      <th>norm.max[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>norm.max[indegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-largest[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-largest[indegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-argmax[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-argmax[indegree over C-&gt;C responses]</th>\n",
+       "      <th>norm.2nd-largest[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over C-&gt;C responses]</th>\n",
+       "      <th>mean[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>mean[indegree over C-&gt;C responses]</th>\n",
+       "      <th>mean-nonzero[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>mean-nonzero[indegree over C-&gt;C responses]</th>\n",
+       "      <th>prop-nonzero[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>prop-nonzero[indegree over C-&gt;C responses]</th>\n",
+       "      <th>prop-multiple[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>prop-multiple[indegree over C-&gt;C responses]</th>\n",
        "      <th>entropy[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>entropy[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>entropy[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>is-present[dyadic interaction motif over mid-thread]</th>\n",
-       "      <th>is-present[dyadic interaction motif]</th>\n",
-       "      <th>is-present[external reciprocity motif over mid-thread]</th>\n",
+       "      <th>entropy[indegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-largest / max[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-largest / max[indegree over C-&gt;C responses]</th>\n",
+       "      <th>is-present[reciprocity motif]</th>\n",
+       "      <th>count[reciprocity motif]</th>\n",
        "      <th>is-present[external reciprocity motif]</th>\n",
-       "      <th>is-present[incoming triads over mid-thread]</th>\n",
+       "      <th>count[external reciprocity motif]</th>\n",
+       "      <th>is-present[dyadic interaction motif]</th>\n",
+       "      <th>count[dyadic interaction motif]</th>\n",
        "      <th>is-present[incoming triads]</th>\n",
-       "      <th>is-present[outgoing triads over mid-thread]</th>\n",
+       "      <th>count[incoming triads]</th>\n",
        "      <th>is-present[outgoing triads]</th>\n",
-       "      <th>is-present[reciprocity motif over mid-thread]</th>\n",
-       "      <th>is-present[reciprocity motif]</th>\n",
-       "      <th>max[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>max[indegree over C-&gt;C responses]</th>\n",
-       "      <th>max[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>max[indegree over C-&gt;c responses]</th>\n",
+       "      <th>count[outgoing triads]</th>\n",
        "      <th>max[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>max[indegree over c-&gt;c responses]</th>\n",
-       "      <th>max[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>max[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>max[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>max[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>mean-nonzero[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>mean-nonzero[indegree over C-&gt;C responses]</th>\n",
-       "      <th>mean-nonzero[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean-nonzero[indegree over C-&gt;c responses]</th>\n",
-       "      <th>mean-nonzero[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean-nonzero[indegree over c-&gt;c responses]</th>\n",
-       "      <th>mean-nonzero[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>mean-nonzero[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>mean-nonzero[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean-nonzero[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>mean[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>mean[indegree over C-&gt;C responses]</th>\n",
-       "      <th>mean[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean[indegree over C-&gt;c responses]</th>\n",
-       "      <th>mean[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean[indegree over c-&gt;c responses]</th>\n",
-       "      <th>mean[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>mean[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>mean[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over C-&gt;C responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over C-&gt;c responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over c-&gt;c responses]</th>\n",
-       "      <th>norm.2nd-largest[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>norm.2nd-largest[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>norm.2nd-largest[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.2nd-largest[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>norm.max[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>norm.max[indegree over C-&gt;C responses]</th>\n",
-       "      <th>norm.max[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.max[indegree over C-&gt;c responses]</th>\n",
+       "      <th>argmax[indegree over c-&gt;c mid-thread responses]</th>\n",
        "      <th>norm.max[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.max[indegree over c-&gt;c responses]</th>\n",
-       "      <th>norm.max[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>norm.max[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>norm.max[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.max[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>prop-multiple[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>prop-multiple[indegree over C-&gt;C responses]</th>\n",
-       "      <th>prop-multiple[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-multiple[indegree over C-&gt;c responses]</th>\n",
-       "      <th>prop-multiple[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-multiple[indegree over c-&gt;c responses]</th>\n",
-       "      <th>prop-multiple[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>prop-multiple[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>prop-multiple[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-multiple[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>prop-nonzero[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>prop-nonzero[indegree over C-&gt;C responses]</th>\n",
-       "      <th>prop-nonzero[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-nonzero[indegree over C-&gt;c responses]</th>\n",
+       "      <th>2nd-largest[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean-nonzero[indegree over c-&gt;c mid-thread responses]</th>\n",
        "      <th>prop-nonzero[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-nonzero[indegree over c-&gt;c responses]</th>\n",
-       "      <th>prop-nonzero[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>prop-nonzero[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>prop-multiple[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>entropy[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>max[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>max[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>argmax[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>argmax[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.max[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.max[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-largest[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-largest[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean-nonzero[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean-nonzero[indegree over C-&gt;c mid-thread responses]</th>\n",
        "      <th>prop-nonzero[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-nonzero[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-nonzero[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>prop-multiple[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>prop-multiple[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>entropy[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>entropy[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>max[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>max[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>argmax[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>argmax[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>norm.max[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>norm.max[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-largest[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-largest[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>mean[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>mean[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>mean-nonzero[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>mean-nonzero[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>prop-nonzero[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>prop-nonzero[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>prop-multiple[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>prop-multiple[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>entropy[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>entropy[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>is-present[reciprocity motif over mid-thread]</th>\n",
+       "      <th>count[reciprocity motif over mid-thread]</th>\n",
+       "      <th>is-present[external reciprocity motif over mid-thread]</th>\n",
+       "      <th>count[external reciprocity motif over mid-thread]</th>\n",
+       "      <th>is-present[dyadic interaction motif over mid-thread]</th>\n",
+       "      <th>count[dyadic interaction motif over mid-thread]</th>\n",
+       "      <th>is-present[incoming triads over mid-thread]</th>\n",
+       "      <th>count[incoming triads over mid-thread]</th>\n",
+       "      <th>is-present[outgoing triads over mid-thread]</th>\n",
+       "      <th>count[outgoing triads over mid-thread]</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>e6p7yrp</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
+       "      <th>e5hm9mp</th>\n",
        "      <td>3.0</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.2</td>\n",
        "      <td>1.0</td>\n",
        "      <td>0.333333</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.111111</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>1.83102</td>\n",
        "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.333333</td>\n",
        "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.111111</td>\n",
+       "      <td>1.8</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.8</td>\n",
+       "      <td>1.285714</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>1.581094</td>\n",
+       "      <td>1.83102</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>0.333333</td>\n",
        "      <td>2.0</td>\n",
        "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.375</td>\n",
        "      <td>2.0</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.073543</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>1.83102</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>1.83102</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.667462</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>1.6</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.6</td>\n",
+       "      <td>0.4</td>\n",
+       "      <td>1.559581</td>\n",
+       "      <td>1.494175</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.666667</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>5.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>3.0</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.5</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.285714</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.375</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.5</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.5</td>\n",
-       "      <td>1.5</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.125</td>\n",
+       "      <td>0.888889</td>\n",
        "      <td>1.333333</td>\n",
        "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>1.667462</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>1.333333</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>0.375</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>1.5</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.125</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.25</td>\n",
        "      <td>0.125</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.625</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.375</td>\n",
-       "      <td>0.5</td>\n",
+       "      <td>1.386294</td>\n",
+       "      <td>1.667462</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.333333</td>\n",
-       "      <td>0.25</td>\n",
-       "      <td>0.25</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.142857</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.428571</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.285714</td>\n",
        "      <td>0.142857</td>\n",
-       "      <td>0.25</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.25</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>1.75</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>1.351784</td>\n",
+       "      <td>1.475076</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.666667</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.666667</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "         2nd-argmax[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                0.0     \n",
-       "\n",
-       "         2nd-argmax[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                       1.0   \n",
+       "         max[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                3.0   \n",
        "\n",
-       "         2nd-argmax[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0     \n",
+       "         argmax[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                   1.0   \n",
        "\n",
-       "         2nd-argmax[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                       1.0   \n",
+       "         norm.max[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                0.333333   \n",
        "\n",
-       "         2nd-argmax[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0     \n",
+       "         2nd-largest[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                        1.0   \n",
        "\n",
        "         2nd-argmax[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                       1.0   \n",
+       "e5hm9mp                                       0.0   \n",
        "\n",
-       "         2nd-argmax[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                2.0      \n",
+       "         norm.2nd-largest[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                        0.111111   \n",
        "\n",
-       "         2nd-argmax[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                        1.0   \n",
+       "         mean[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                 0.9   \n",
        "\n",
-       "         2nd-argmax[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                2.0      \n",
+       "         mean-nonzero[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                    1.285714   \n",
        "\n",
-       "         2nd-argmax[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                        3.0   \n",
+       "         prop-nonzero[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                         0.7   \n",
        "\n",
-       "         2nd-largest / max[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.333333            \n",
+       "         prop-multiple[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                     0.142857   \n",
        "\n",
-       "         2nd-largest / max[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                              0.2   \n",
+       "         entropy[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                1.83102   \n",
        "\n",
-       "         2nd-largest / max[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0            \n",
+       "         2nd-largest / max[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                         0.333333   \n",
        "\n",
-       "         2nd-largest / max[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                         0.333333   \n",
+       "         max[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                 2.0   \n",
        "\n",
-       "         2nd-largest / max[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0            \n",
+       "         max[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                3.0   \n",
        "\n",
-       "         2nd-largest / max[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                         0.333333   \n",
+       "         argmax[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                    0.0   \n",
        "\n",
-       "         2nd-largest / max[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.333333             \n",
+       "         argmax[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                   1.0   \n",
        "\n",
-       "         2nd-largest / max[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                          0.333333   \n",
+       "         norm.max[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                 0.222222   \n",
        "\n",
-       "         2nd-largest / max[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.333333             \n",
+       "         norm.max[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                0.333333   \n",
        "\n",
-       "         2nd-largest / max[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                          0.666667   \n",
+       "         2nd-largest[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                         2.0   \n",
        "\n",
-       "         2nd-largest[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0      \n",
+       "         2nd-largest[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                        1.0   \n",
        "\n",
-       "         2nd-largest[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                        1.0   \n",
+       "         2nd-argmax[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                        2.0   \n",
        "\n",
-       "         2nd-largest[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0      \n",
+       "         2nd-argmax[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                       0.0   \n",
        "\n",
-       "         2nd-largest[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                        1.0   \n",
+       "         norm.2nd-largest[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                         0.222222   \n",
        "\n",
-       "         2nd-largest[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0      \n",
+       "         norm.2nd-largest[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                        0.111111   \n",
        "\n",
-       "         2nd-largest[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                        1.0   \n",
+       "         mean[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                  1.8   \n",
        "\n",
-       "         2nd-largest[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0       \n",
+       "         mean[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                 0.9   \n",
        "\n",
-       "         2nd-largest[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                         1.0   \n",
+       "         mean-nonzero[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                          1.8   \n",
        "\n",
-       "         2nd-largest[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0       \n",
+       "         mean-nonzero[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                    1.285714   \n",
        "\n",
-       "         2nd-largest[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                         2.0   \n",
+       "         prop-nonzero[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                          1.0   \n",
        "\n",
-       "         argmax[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                              1.0   \n",
+       "         prop-nonzero[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                         0.7   \n",
        "\n",
-       "         argmax[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                   0.0   \n",
+       "         prop-multiple[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                           0.8   \n",
        "\n",
-       "         argmax[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                              0.0   \n",
+       "         prop-multiple[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                     0.142857   \n",
        "\n",
-       "         argmax[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                   0.0   \n",
+       "         entropy[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                1.581094   \n",
        "\n",
-       "         argmax[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                              0.0   \n",
+       "         entropy[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                1.83102   \n",
        "\n",
-       "         argmax[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                   0.0   \n",
+       "         2nd-largest / max[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                               1.0   \n",
        "\n",
-       "         argmax[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                               1.0   \n",
+       "         2nd-largest / max[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                         0.333333   \n",
+       "\n",
+       "         max[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                 2.0   \n",
+       "\n",
+       "         max[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                3.0   \n",
        "\n",
        "         argmax[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                    0.0   \n",
+       "e5hm9mp                                    0.0   \n",
        "\n",
-       "         argmax[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                               1.0   \n",
+       "         argmax[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                   1.0   \n",
        "\n",
-       "         argmax[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                    0.0   \n",
+       "         norm.max[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                     0.25   \n",
        "\n",
-       "         count[dyadic interaction motif over mid-thread]  \\\n",
-       "e6p7yrp                                              2.0   \n",
+       "         norm.max[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                   0.375   \n",
        "\n",
-       "         count[dyadic interaction motif]  \\\n",
-       "e6p7yrp                              3.0   \n",
+       "         2nd-largest[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                         2.0   \n",
        "\n",
-       "         count[external reciprocity motif over mid-thread]  \\\n",
-       "e6p7yrp                                                2.0   \n",
+       "         2nd-largest[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                        2.0   \n",
        "\n",
-       "         count[external reciprocity motif]  \\\n",
-       "e6p7yrp                                2.0   \n",
+       "         2nd-argmax[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                        2.0   \n",
        "\n",
-       "         count[incoming triads over mid-thread]  count[incoming triads]  \\\n",
-       "e6p7yrp                                     3.0                    10.0   \n",
+       "         2nd-argmax[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                       0.0   \n",
        "\n",
-       "         count[outgoing triads over mid-thread]  count[outgoing triads]  \\\n",
-       "e6p7yrp                                     3.0                     3.0   \n",
+       "         norm.2nd-largest[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                             0.25   \n",
        "\n",
-       "         count[reciprocity motif over mid-thread]  count[reciprocity motif]  \\\n",
-       "e6p7yrp                                       2.0                       4.0   \n",
+       "         norm.2nd-largest[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                            0.25   \n",
        "\n",
-       "         entropy[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                          1.242453   \n",
+       "         mean[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                  1.6   \n",
        "\n",
-       "         entropy[indegree over C->C responses]  \\\n",
-       "e6p7yrp                               1.073543   \n",
+       "         mean[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                 1.6   \n",
        "\n",
-       "         entropy[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                          1.791759   \n",
+       "         mean-nonzero[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                          1.6   \n",
        "\n",
-       "         entropy[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                1.83102   \n",
+       "         mean-nonzero[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                         1.6   \n",
        "\n",
-       "         entropy[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                          1.791759   \n",
+       "         prop-nonzero[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                          1.0   \n",
        "\n",
-       "         entropy[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                1.83102   \n",
+       "         prop-nonzero[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                         1.0   \n",
        "\n",
-       "         entropy[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.242453   \n",
+       "         prop-multiple[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                           0.6   \n",
        "\n",
-       "         entropy[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                1.667462   \n",
+       "         prop-multiple[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                          0.4   \n",
        "\n",
-       "         entropy[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.242453   \n",
+       "         entropy[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                1.559581   \n",
        "\n",
-       "         entropy[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                1.676988   \n",
+       "         entropy[indegree over C->C responses]  \\\n",
+       "e5hm9mp                               1.494175   \n",
        "\n",
-       "         is-present[dyadic interaction motif over mid-thread]  \\\n",
-       "e6p7yrp                                                1.0      \n",
+       "         2nd-largest / max[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                               1.0   \n",
        "\n",
-       "         is-present[dyadic interaction motif]  \\\n",
-       "e6p7yrp                                   1.0   \n",
+       "         2nd-largest / max[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                         0.666667   \n",
        "\n",
-       "         is-present[external reciprocity motif over mid-thread]  \\\n",
-       "e6p7yrp                                                1.0        \n",
+       "         is-present[reciprocity motif]  count[reciprocity motif]  \\\n",
+       "e5hm9mp                            1.0                       4.0   \n",
        "\n",
        "         is-present[external reciprocity motif]  \\\n",
-       "e6p7yrp                                     1.0   \n",
-       "\n",
-       "         is-present[incoming triads over mid-thread]  \\\n",
-       "e6p7yrp                                          1.0   \n",
+       "e5hm9mp                                     1.0   \n",
        "\n",
-       "         is-present[incoming triads]  \\\n",
-       "e6p7yrp                          1.0   \n",
+       "         count[external reciprocity motif]  \\\n",
+       "e5hm9mp                                4.0   \n",
        "\n",
-       "         is-present[outgoing triads over mid-thread]  \\\n",
-       "e6p7yrp                                          1.0   \n",
+       "         is-present[dyadic interaction motif]  \\\n",
+       "e5hm9mp                                   1.0   \n",
        "\n",
-       "         is-present[outgoing triads]  \\\n",
-       "e6p7yrp                          1.0   \n",
+       "         count[dyadic interaction motif]  is-present[incoming triads]  \\\n",
+       "e5hm9mp                              3.0                          1.0   \n",
        "\n",
-       "         is-present[reciprocity motif over mid-thread]  \\\n",
-       "e6p7yrp                                            1.0   \n",
+       "         count[incoming triads]  is-present[outgoing triads]  \\\n",
+       "e5hm9mp                     4.0                          1.0   \n",
        "\n",
-       "         is-present[reciprocity motif]  \\\n",
-       "e6p7yrp                            1.0   \n",
+       "         count[outgoing triads]  max[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                     3.0                                           3.0   \n",
        "\n",
-       "         max[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           3.0   \n",
+       "         argmax[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                              0.0   \n",
        "\n",
-       "         max[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                5.0   \n",
+       "         norm.max[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                              0.375   \n",
        "\n",
-       "         max[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.0   \n",
+       "         2nd-largest[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0      \n",
        "\n",
-       "         max[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                3.0   \n",
+       "         2nd-argmax[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0     \n",
        "\n",
-       "         max[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.0   \n",
+       "         norm.2nd-largest[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                              0.125           \n",
        "\n",
-       "         max[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                3.0   \n",
+       "         mean[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                       0.888889   \n",
        "\n",
-       "         max[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                            3.0   \n",
+       "         mean-nonzero[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.333333       \n",
        "\n",
-       "         max[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                 3.0   \n",
+       "         prop-nonzero[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.666667       \n",
        "\n",
-       "         max[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                            3.0   \n",
+       "         prop-multiple[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.166667        \n",
        "\n",
-       "         max[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                 3.0   \n",
+       "         entropy[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                          1.667462   \n",
        "\n",
-       "         mean-nonzero[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.5       \n",
+       "         2nd-largest / max[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.333333            \n",
        "\n",
-       "         mean-nonzero[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                         2.0   \n",
+       "         max[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                            2.0   \n",
        "\n",
-       "         mean-nonzero[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0       \n",
+       "         max[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           3.0   \n",
        "\n",
-       "         mean-nonzero[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                    1.285714   \n",
+       "         argmax[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                               1.0   \n",
        "\n",
-       "         mean-nonzero[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0       \n",
+       "         argmax[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                              0.0   \n",
        "\n",
-       "         mean-nonzero[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                    1.285714   \n",
+       "         norm.max[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                               0.25    \n",
        "\n",
-       "         mean-nonzero[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.5        \n",
+       "         norm.max[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                              0.375   \n",
        "\n",
-       "         mean-nonzero[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                     1.333333   \n",
+       "         2nd-largest[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                2.0       \n",
        "\n",
-       "         mean-nonzero[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.5        \n",
+       "         2nd-largest[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0      \n",
        "\n",
-       "         mean-nonzero[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                          1.5   \n",
+       "         2nd-argmax[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                2.0      \n",
        "\n",
-       "         mean[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                            1.0   \n",
+       "         2nd-argmax[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0     \n",
        "\n",
-       "         mean[indegree over C->C responses]  \\\n",
-       "e6p7yrp                            1.333333   \n",
+       "         norm.2nd-largest[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                               0.25            \n",
        "\n",
-       "         mean[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                       0.666667   \n",
+       "         norm.2nd-largest[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                              0.125           \n",
        "\n",
-       "         mean[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                 0.9   \n",
+       "         mean[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                             1.6   \n",
        "\n",
-       "         mean[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                       0.666667   \n",
+       "         mean[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                       0.888889   \n",
        "\n",
-       "         mean[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                 0.9   \n",
+       "         mean-nonzero[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                2.0        \n",
        "\n",
-       "         mean[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                             1.0   \n",
+       "         mean-nonzero[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.333333       \n",
        "\n",
-       "         mean[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                             1.333333   \n",
+       "         prop-nonzero[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                0.8        \n",
        "\n",
-       "         mean[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                             1.0   \n",
+       "         prop-nonzero[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.666667       \n",
        "\n",
-       "         mean[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                  1.5   \n",
+       "         prop-multiple[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0         \n",
        "\n",
-       "         norm.2nd-largest[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667           \n",
+       "         prop-multiple[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.166667        \n",
        "\n",
-       "         norm.2nd-largest[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                           0.125   \n",
+       "         entropy[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.386294   \n",
        "\n",
-       "         norm.2nd-largest[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667           \n",
+       "         entropy[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                          1.667462   \n",
        "\n",
-       "         norm.2nd-largest[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                        0.111111   \n",
+       "         2nd-largest / max[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0             \n",
        "\n",
-       "         norm.2nd-largest[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667           \n",
+       "         2nd-largest / max[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.333333            \n",
        "\n",
-       "         norm.2nd-largest[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                        0.111111   \n",
+       "         max[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                            2.0   \n",
        "\n",
-       "         norm.2nd-largest[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667            \n",
+       "         max[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           3.0   \n",
        "\n",
-       "         norm.2nd-largest[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                            0.125   \n",
+       "         argmax[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                               1.0   \n",
        "\n",
-       "         norm.2nd-largest[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667            \n",
+       "         argmax[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                              0.0   \n",
        "\n",
-       "         norm.2nd-largest[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                         0.222222   \n",
+       "         norm.max[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.285714    \n",
        "\n",
        "         norm.max[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                0.5   \n",
-       "\n",
-       "         norm.max[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                   0.625   \n",
+       "e5hm9mp                                           0.428571   \n",
        "\n",
-       "         norm.max[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667   \n",
+       "         2nd-largest[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                2.0       \n",
        "\n",
-       "         norm.max[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                0.333333   \n",
+       "         2nd-largest[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0      \n",
        "\n",
-       "         norm.max[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667   \n",
+       "         2nd-argmax[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                2.0      \n",
        "\n",
-       "         norm.max[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                0.333333   \n",
+       "         2nd-argmax[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0     \n",
        "\n",
-       "         norm.max[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                0.5    \n",
+       "         norm.2nd-largest[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.285714            \n",
        "\n",
-       "         norm.max[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                    0.375   \n",
+       "         norm.2nd-largest[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.142857           \n",
        "\n",
-       "         norm.max[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                0.5    \n",
+       "         mean[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                             1.4   \n",
        "\n",
-       "         norm.max[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                 0.333333   \n",
+       "         mean[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                            1.4   \n",
        "\n",
-       "         prop-multiple[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                               0.25        \n",
+       "         mean-nonzero[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                               1.75        \n",
        "\n",
-       "         prop-multiple[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                         0.25   \n",
+       "         mean-nonzero[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.4       \n",
        "\n",
-       "         prop-multiple[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                0.0        \n",
+       "         prop-nonzero[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                0.8        \n",
        "\n",
-       "         prop-multiple[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                     0.142857   \n",
+       "         prop-nonzero[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0       \n",
        "\n",
-       "         prop-multiple[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                0.0        \n",
+       "         prop-multiple[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                               0.75         \n",
        "\n",
-       "         prop-multiple[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                     0.142857   \n",
+       "         prop-multiple[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                0.2        \n",
        "\n",
-       "         prop-multiple[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                               0.25         \n",
+       "         entropy[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.351784   \n",
        "\n",
-       "         prop-multiple[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                      0.166667   \n",
+       "         entropy[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                          1.475076   \n",
        "\n",
-       "         prop-multiple[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                               0.25         \n",
+       "         2nd-largest / max[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0             \n",
        "\n",
-       "         prop-multiple[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                      0.333333   \n",
+       "         2nd-largest / max[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.333333            \n",
        "\n",
-       "         prop-nonzero[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.666667       \n",
+       "         is-present[reciprocity motif over mid-thread]  \\\n",
+       "e5hm9mp                                            1.0   \n",
        "\n",
-       "         prop-nonzero[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                    0.666667   \n",
+       "         count[reciprocity motif over mid-thread]  \\\n",
+       "e5hm9mp                                       3.0   \n",
        "\n",
-       "         prop-nonzero[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.666667       \n",
+       "         is-present[external reciprocity motif over mid-thread]  \\\n",
+       "e5hm9mp                                                1.0        \n",
        "\n",
-       "         prop-nonzero[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                         0.7   \n",
+       "         count[external reciprocity motif over mid-thread]  \\\n",
+       "e5hm9mp                                                2.0   \n",
        "\n",
-       "         prop-nonzero[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.666667       \n",
+       "         is-present[dyadic interaction motif over mid-thread]  \\\n",
+       "e5hm9mp                                                1.0      \n",
        "\n",
-       "         prop-nonzero[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                         0.7   \n",
+       "         count[dyadic interaction motif over mid-thread]  \\\n",
+       "e5hm9mp                                              2.0   \n",
        "\n",
-       "         prop-nonzero[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.666667        \n",
+       "         is-present[incoming triads over mid-thread]  \\\n",
+       "e5hm9mp                                          1.0   \n",
        "\n",
-       "         prop-nonzero[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                          1.0   \n",
+       "         count[incoming triads over mid-thread]  \\\n",
+       "e5hm9mp                                     3.0   \n",
        "\n",
-       "         prop-nonzero[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.666667        \n",
+       "         is-present[outgoing triads over mid-thread]  \\\n",
+       "e5hm9mp                                          1.0   \n",
        "\n",
-       "         prop-nonzero[outdegree over C->c responses]  \n",
-       "e6p7yrp                                          1.0  "
+       "         count[outgoing triads over mid-thread]  \n",
+       "e5hm9mp                                     3.0  "
       ]
      },
-     "execution_count": 23,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1218,7 +1213,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -1242,600 +1237,567 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>2nd-argmax[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-argmax[indegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-argmax[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-argmax[indegree over C-&gt;c responses]</th>\n",
-       "      <th>2nd-argmax[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>max[indegree over c-&gt;c responses]</th>\n",
+       "      <th>argmax[indegree over c-&gt;c responses]</th>\n",
+       "      <th>norm.max[indegree over c-&gt;c responses]</th>\n",
+       "      <th>2nd-largest[indegree over c-&gt;c responses]</th>\n",
        "      <th>2nd-argmax[indegree over c-&gt;c responses]</th>\n",
-       "      <th>2nd-argmax[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-argmax[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-argmax[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-argmax[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>2nd-largest / max[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-largest / max[indegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-largest / max[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-largest / max[indegree over C-&gt;c responses]</th>\n",
-       "      <th>2nd-largest / max[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over c-&gt;c responses]</th>\n",
+       "      <th>mean[indegree over c-&gt;c responses]</th>\n",
+       "      <th>mean-nonzero[indegree over c-&gt;c responses]</th>\n",
+       "      <th>prop-nonzero[indegree over c-&gt;c responses]</th>\n",
+       "      <th>prop-multiple[indegree over c-&gt;c responses]</th>\n",
+       "      <th>entropy[indegree over c-&gt;c responses]</th>\n",
        "      <th>2nd-largest / max[indegree over c-&gt;c responses]</th>\n",
-       "      <th>2nd-largest / max[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-largest / max[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-largest / max[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-largest / max[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>2nd-largest[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-largest[indegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-largest[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>max[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>max[indegree over C-&gt;c responses]</th>\n",
+       "      <th>argmax[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>argmax[indegree over C-&gt;c responses]</th>\n",
+       "      <th>norm.max[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>norm.max[indegree over C-&gt;c responses]</th>\n",
+       "      <th>2nd-largest[outdegree over C-&gt;c responses]</th>\n",
        "      <th>2nd-largest[indegree over C-&gt;c responses]</th>\n",
-       "      <th>2nd-largest[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-largest[indegree over c-&gt;c responses]</th>\n",
-       "      <th>2nd-largest[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>2nd-largest[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>2nd-largest[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>2nd-largest[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>argmax[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>argmax[indegree over C-&gt;C responses]</th>\n",
-       "      <th>argmax[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>argmax[indegree over C-&gt;c responses]</th>\n",
-       "      <th>argmax[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>argmax[indegree over c-&gt;c responses]</th>\n",
-       "      <th>argmax[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>argmax[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>argmax[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>argmax[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>count[dyadic interaction motif over mid-thread]</th>\n",
-       "      <th>count[dyadic interaction motif]</th>\n",
-       "      <th>count[external reciprocity motif over mid-thread]</th>\n",
-       "      <th>count[external reciprocity motif]</th>\n",
-       "      <th>count[incoming triads over mid-thread]</th>\n",
-       "      <th>count[incoming triads]</th>\n",
-       "      <th>count[outgoing triads over mid-thread]</th>\n",
-       "      <th>count[outgoing triads]</th>\n",
-       "      <th>count[reciprocity motif over mid-thread]</th>\n",
-       "      <th>count[reciprocity motif]</th>\n",
-       "      <th>entropy[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>entropy[indegree over C-&gt;C responses]</th>\n",
-       "      <th>entropy[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>2nd-argmax[indegree over C-&gt;c responses]</th>\n",
+       "      <th>norm.2nd-largest[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over C-&gt;c responses]</th>\n",
+       "      <th>mean[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>mean[indegree over C-&gt;c responses]</th>\n",
+       "      <th>mean-nonzero[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>mean-nonzero[indegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-nonzero[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-nonzero[indegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-multiple[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-multiple[indegree over C-&gt;c responses]</th>\n",
+       "      <th>entropy[outdegree over C-&gt;c responses]</th>\n",
        "      <th>entropy[indegree over C-&gt;c responses]</th>\n",
-       "      <th>entropy[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>entropy[indegree over c-&gt;c responses]</th>\n",
-       "      <th>entropy[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>2nd-largest / max[indegree over C-&gt;c responses]</th>\n",
+       "      <th>max[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>max[indegree over C-&gt;C responses]</th>\n",
+       "      <th>argmax[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>argmax[indegree over C-&gt;C responses]</th>\n",
+       "      <th>norm.max[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>norm.max[indegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-largest[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-largest[indegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-argmax[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-argmax[indegree over C-&gt;C responses]</th>\n",
+       "      <th>norm.2nd-largest[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over C-&gt;C responses]</th>\n",
+       "      <th>mean[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>mean[indegree over C-&gt;C responses]</th>\n",
+       "      <th>mean-nonzero[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>mean-nonzero[indegree over C-&gt;C responses]</th>\n",
+       "      <th>prop-nonzero[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>prop-nonzero[indegree over C-&gt;C responses]</th>\n",
+       "      <th>prop-multiple[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>prop-multiple[indegree over C-&gt;C responses]</th>\n",
        "      <th>entropy[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>entropy[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>entropy[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>is-present[dyadic interaction motif over mid-thread]</th>\n",
-       "      <th>is-present[dyadic interaction motif]</th>\n",
-       "      <th>is-present[external reciprocity motif over mid-thread]</th>\n",
+       "      <th>entropy[indegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-largest / max[outdegree over C-&gt;C responses]</th>\n",
+       "      <th>2nd-largest / max[indegree over C-&gt;C responses]</th>\n",
+       "      <th>is-present[reciprocity motif]</th>\n",
+       "      <th>count[reciprocity motif]</th>\n",
        "      <th>is-present[external reciprocity motif]</th>\n",
-       "      <th>is-present[incoming triads over mid-thread]</th>\n",
+       "      <th>count[external reciprocity motif]</th>\n",
+       "      <th>is-present[dyadic interaction motif]</th>\n",
+       "      <th>count[dyadic interaction motif]</th>\n",
        "      <th>is-present[incoming triads]</th>\n",
-       "      <th>is-present[outgoing triads over mid-thread]</th>\n",
+       "      <th>count[incoming triads]</th>\n",
        "      <th>is-present[outgoing triads]</th>\n",
-       "      <th>is-present[reciprocity motif over mid-thread]</th>\n",
-       "      <th>is-present[reciprocity motif]</th>\n",
-       "      <th>max[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>max[indegree over C-&gt;C responses]</th>\n",
-       "      <th>max[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>max[indegree over C-&gt;c responses]</th>\n",
+       "      <th>count[outgoing triads]</th>\n",
        "      <th>max[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>max[indegree over c-&gt;c responses]</th>\n",
-       "      <th>max[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>max[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>max[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>max[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>mean-nonzero[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>mean-nonzero[indegree over C-&gt;C responses]</th>\n",
-       "      <th>mean-nonzero[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean-nonzero[indegree over C-&gt;c responses]</th>\n",
-       "      <th>mean-nonzero[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean-nonzero[indegree over c-&gt;c responses]</th>\n",
-       "      <th>mean-nonzero[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>mean-nonzero[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>mean-nonzero[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean-nonzero[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>mean[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>mean[indegree over C-&gt;C responses]</th>\n",
-       "      <th>mean[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean[indegree over C-&gt;c responses]</th>\n",
-       "      <th>mean[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean[indegree over c-&gt;c responses]</th>\n",
-       "      <th>mean[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>mean[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>mean[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>mean[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over C-&gt;C responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over C-&gt;c responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.2nd-largest[indegree over c-&gt;c responses]</th>\n",
-       "      <th>norm.2nd-largest[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>norm.2nd-largest[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>norm.2nd-largest[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.2nd-largest[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>norm.max[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>norm.max[indegree over C-&gt;C responses]</th>\n",
-       "      <th>norm.max[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.max[indegree over C-&gt;c responses]</th>\n",
+       "      <th>argmax[indegree over c-&gt;c mid-thread responses]</th>\n",
        "      <th>norm.max[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.max[indegree over c-&gt;c responses]</th>\n",
-       "      <th>norm.max[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>norm.max[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>norm.max[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>norm.max[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>prop-multiple[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>prop-multiple[indegree over C-&gt;C responses]</th>\n",
-       "      <th>prop-multiple[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-multiple[indegree over C-&gt;c responses]</th>\n",
+       "      <th>2nd-largest[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean-nonzero[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>prop-nonzero[indegree over c-&gt;c mid-thread responses]</th>\n",
        "      <th>prop-multiple[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-multiple[indegree over c-&gt;c responses]</th>\n",
-       "      <th>prop-multiple[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>prop-multiple[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>prop-multiple[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-multiple[outdegree over C-&gt;c responses]</th>\n",
-       "      <th>prop-nonzero[indegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>prop-nonzero[indegree over C-&gt;C responses]</th>\n",
+       "      <th>entropy[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>max[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>max[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>argmax[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>argmax[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.max[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.max[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-largest[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-largest[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean-nonzero[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>mean-nonzero[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>prop-nonzero[outdegree over C-&gt;c mid-thread responses]</th>\n",
        "      <th>prop-nonzero[indegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-nonzero[indegree over C-&gt;c responses]</th>\n",
-       "      <th>prop-nonzero[indegree over c-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-nonzero[indegree over c-&gt;c responses]</th>\n",
+       "      <th>prop-multiple[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>prop-multiple[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>entropy[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>entropy[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[outdegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[indegree over C-&gt;c mid-thread responses]</th>\n",
+       "      <th>max[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>max[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>argmax[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>argmax[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>norm.max[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>norm.max[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-largest[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-largest[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-argmax[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>norm.2nd-largest[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>mean[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>mean[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>mean-nonzero[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>mean-nonzero[indegree over C-&gt;C mid-thread responses]</th>\n",
        "      <th>prop-nonzero[outdegree over C-&gt;C mid-thread responses]</th>\n",
-       "      <th>prop-nonzero[outdegree over C-&gt;C responses]</th>\n",
-       "      <th>prop-nonzero[outdegree over C-&gt;c mid-thread responses]</th>\n",
-       "      <th>prop-nonzero[outdegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-nonzero[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>prop-multiple[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>prop-multiple[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>entropy[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>entropy[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[outdegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>2nd-largest / max[indegree over C-&gt;C mid-thread responses]</th>\n",
+       "      <th>is-present[reciprocity motif over mid-thread]</th>\n",
+       "      <th>count[reciprocity motif over mid-thread]</th>\n",
+       "      <th>is-present[external reciprocity motif over mid-thread]</th>\n",
+       "      <th>count[external reciprocity motif over mid-thread]</th>\n",
+       "      <th>is-present[dyadic interaction motif over mid-thread]</th>\n",
+       "      <th>count[dyadic interaction motif over mid-thread]</th>\n",
+       "      <th>is-present[incoming triads over mid-thread]</th>\n",
+       "      <th>count[incoming triads over mid-thread]</th>\n",
+       "      <th>is-present[outgoing triads over mid-thread]</th>\n",
+       "      <th>count[outgoing triads over mid-thread]</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>e6p7yrp</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <th>e5hm9mp</th>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.333333</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.111111</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>1.831020</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.333333</td>\n",
        "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.111111</td>\n",
+       "      <td>1.800000</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.800000</td>\n",
+       "      <td>1.285714</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>1.581094</td>\n",
+       "      <td>1.831020</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.375000</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>1.559581</td>\n",
+       "      <td>1.494175</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.666667</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>0.375000</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
+       "      <td>0.125000</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>1.667462</td>\n",
+       "      <td>0.333333</td>\n",
        "      <td>2.0</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.375000</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.073543</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>1.831020</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>1.831020</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.667462</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.676988</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.125000</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>1.386294</td>\n",
+       "      <td>1.667462</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.428571</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>1.750000</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.750000</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>1.351784</td>\n",
+       "      <td>1.475076</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.333333</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>5.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>e5ytz1d</th>\n",
        "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.333333</td>\n",
        "      <td>3.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>2.250000</td>\n",
+       "      <td>0.4</td>\n",
+       "      <td>0.750000</td>\n",
+       "      <td>1.310784</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.111111</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.500000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.111111</td>\n",
+       "      <td>0.333333</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
        "      <td>0.9</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>1.333333</td>\n",
+       "      <td>2.250000</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.142857</td>\n",
+       "      <td>0.4</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.666667</td>\n",
+       "      <td>0.750000</td>\n",
+       "      <td>2.197225</td>\n",
+       "      <td>1.310784</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
        "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5ywqyk</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
+       "      <td>0.111111</td>\n",
+       "      <td>0.333333</td>\n",
        "      <td>1.0</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.750000</td>\n",
        "      <td>1.0</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>0.111111</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.250000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.444444</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.750000</td>\n",
+       "      <td>2.197225</td>\n",
+       "      <td>1.310784</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>5.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>7.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1.011404</td>\n",
+       "      <td>0.666667</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>0.500000</td>\n",
        "      <td>1.0</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1.791759</td>\n",
+       "      <td>1.011404</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
+       "      <td>0.666667</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>0.500000</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.054920</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>0.974315</td>\n",
-       "      <td>1.214890</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
        "      <td>2.0</td>\n",
        "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.666667</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.666667</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>1.250000</td>\n",
        "      <td>2.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.333333</td>\n",
        "      <td>0.666667</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
        "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
+       "      <td>0.000000</td>\n",
        "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
+       "      <td>1.791759</td>\n",
+       "      <td>1.011404</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>e5qv9rj</th>\n",
+       "      <th>e6ls80j</th>\n",
+       "      <td>4.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.444444</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>2.250000</td>\n",
+       "      <td>0.4</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>1.214890</td>\n",
+       "      <td>0.750000</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>3.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.444444</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.500000</td>\n",
+       "      <td>2.250000</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.4</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>1.676988</td>\n",
+       "      <td>1.214890</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.750000</td>\n",
        "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.444444</td>\n",
        "      <td>2.0</td>\n",
        "      <td>3.0</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.222222</td>\n",
        "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>1.500000</td>\n",
+       "      <td>2.250000</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.571429</td>\n",
        "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>1.676988</td>\n",
+       "      <td>1.214890</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.750000</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>9.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
+       "      <td>0.600000</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>0.555556</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.950271</td>\n",
+       "      <td>0.333333</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>6.0</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.464816</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.464816</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.464816</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.600000</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.555556</td>\n",
+       "      <td>1.250000</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1.332179</td>\n",
+       "      <td>0.950271</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>3.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.600000</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.900000</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>0.833333</td>\n",
+       "      <td>1.250000</td>\n",
+       "      <td>1.666667</td>\n",
        "      <td>0.666667</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.166667</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.250000</td>\n",
        "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
+       "      <td>1.332179</td>\n",
+       "      <td>0.950271</td>\n",
        "      <td>0.5</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6jhojf</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
        "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
@@ -1843,8270 +1805,1153 @@
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>e5mhgl5</th>\n",
        "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>1.889159</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>6.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>6.0</td>\n",
-       "      <td>3.0</td>\n",
        "      <td>4.0</td>\n",
-       "      <td>1.475076</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.153742</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.213008</td>\n",
-       "      <td>1.427061</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>1.125000</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>0.875000</td>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>1.889159</td>\n",
+       "      <td>1.889159</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.250000</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.125000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.142857</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>0.875000</td>\n",
+       "      <td>0.750000</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1.906155</td>\n",
+       "      <td>1.732868</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>1.000000</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>6.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.250000</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1.732868</td>\n",
+       "      <td>1.000000</td>\n",
        "      <td>2.0</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.500000</td>\n",
        "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
        "      <td>0.250000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
+       "      <td>1.142857</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1.732868</td>\n",
+       "      <td>1.732868</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>1.000000</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>0.285714</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.800000</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.800000</td>\n",
+       "      <td>1.166667</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>1.747868</td>\n",
+       "      <td>1.549826</td>\n",
+       "      <td>0.5</td>\n",
        "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6989ii</th>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>e6w6fah</th>\n",
+       "      <td>9.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>9.000000</td>\n",
+       "      <td>0.1</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "      <td>1.0</td>\n",
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        "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
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        "      <td>1.0</td>\n",
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        "      <td>1.0</td>\n",
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+       "      <td>0.888889</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>8.000000</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.079442</td>\n",
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+       "      <td>1.000000</td>\n",
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        "      <td>1.0</td>\n",
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        "      <td>1.0</td>\n",
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        "      <td>1.0</td>\n",
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        "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
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+       "      <td>0.888889</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>8.000000</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>0.111111</td>\n",
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+       "      <td>1.000000</td>\n",
+       "      <td>2.079442</td>\n",
+       "      <td>0.000000</td>\n",
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        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>6.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>28.0</td>\n",
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        "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
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+       "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
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        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>1.945910</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.682908</td>\n",
-       "      <td>0.693147</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
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        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
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-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
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-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>3.500000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
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-       "      <td>3.500000</td>\n",
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-       "      <td>0.500000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
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-       "      <td>0.500000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
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-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.500000</td>\n",
+       "      <td>NaN</td>\n",
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        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.142857</td>\n",
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-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
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-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e69lgse</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
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-       "      <td>2.0</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
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-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
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-       "      <td>1.0</td>\n",
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-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
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-       "      <td>2.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.255482</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.464816</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.464816</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.714286</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.714286</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5kwkg2</th>\n",
-       "      <td>1.0</td>\n",
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-       "      <td>2.0</td>\n",
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-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
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-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>6.0</td>\n",
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-       "      <td>4.0</td>\n",
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-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6mehe7</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.213008</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>0.950271</td>\n",
-       "      <td>1.667462</td>\n",
-       "      <td>1.011404</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.666667</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6m0hsd</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>0.974315</td>\n",
-       "      <td>0.936888</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e64r385</th>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.714286</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>0.875000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5surbt</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.303092</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.303092</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.303092</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e58gxii</th>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.213008</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.475076</td>\n",
-       "      <td>1.667462</td>\n",
-       "      <td>1.475076</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e64vc8y</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.002718</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.002718</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.002718</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e57504g</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.714286</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>0.875000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5borjq</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.945910</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.945910</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e64n9zv</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.082196</td>\n",
-       "      <td>1.060857</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e582ud3</th>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>16.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.636514</td>\n",
-       "      <td>0.848686</td>\n",
-       "      <td>0.636514</td>\n",
-       "      <td>0.848686</td>\n",
-       "      <td>0.636514</td>\n",
-       "      <td>0.848686</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.300000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.3</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.3</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e64i9cf</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>0.955700</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>0.950271</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.333333</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.666667</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6q9204</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.011404</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.475076</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.833333</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5modd7</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.273028</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.273028</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.273028</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5xhbyd</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.320888</td>\n",
-       "      <td>1.310784</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5oaf7h</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>0.562335</td>\n",
-       "      <td>0.562335</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>0.974315</td>\n",
-       "      <td>0.936888</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6nir3u</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>1.945910</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.682908</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>3.500000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>3.500000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6c3xdn</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5d3zaa</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.054920</td>\n",
-       "      <td>1.351784</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.666667</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>0.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5gnjv9</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>28.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.348832</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.348832</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.348832</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>4.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>4.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>4.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.888889</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e69gw2t</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.054920</td>\n",
-       "      <td>1.351784</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.464816</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.666667</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5syrih</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.273028</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5sa2yf</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.686962</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>4.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>4.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6ai7z5</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>1.831020</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>1.831020</td>\n",
-       "      <td>0.867563</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>0.867563</td>\n",
-       "      <td>1.303092</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
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-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5smhzk</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.945910</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.945910</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.636514</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>0.682908</td>\n",
-       "      <td>0.964963</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>3.500000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.333333</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5v91s0</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.149060</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.149060</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.149060</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6n6di6</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.213008</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>0.888889</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6iqq30</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.002718</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.002718</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.002718</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5bfad7</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.273028</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6x5he5</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>4.000000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6l9uyf</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.149060</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.149060</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.149060</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.888889</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e57hyr1</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.714286</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>0.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5b8sj7</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.636514</td>\n",
-       "      <td>1.060857</td>\n",
-       "      <td>1.011404</td>\n",
-       "      <td>1.310784</td>\n",
-       "      <td>1.011404</td>\n",
-       "      <td>1.310784</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6nlep7</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>36.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>9.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>9.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>9.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.100000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.1</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.1</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6ltazd</th>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.500402</td>\n",
-       "      <td>0.867563</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.581094</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.581094</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.464816</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.500000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.833333</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e57a6qq</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.011404</td>\n",
-       "      <td>1.011404</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.889159</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.464816</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5qc7eb</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.011404</td>\n",
-       "      <td>1.004242</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>2.333333</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6hqt5y</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>12.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.500402</td>\n",
-       "      <td>0.964963</td>\n",
-       "      <td>0.500402</td>\n",
-       "      <td>0.964963</td>\n",
-       "      <td>0.500402</td>\n",
-       "      <td>0.964963</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.500000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>2.500000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>2.500000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.3</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.3</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.888889</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5ua84v</th>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.213008</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.714286</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e65m7kq</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.950271</td>\n",
-       "      <td>1.214890</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.666667</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.888889</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5ggtru</th>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.900256</td>\n",
-       "      <td>1.149060</td>\n",
-       "      <td>1.213008</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.213008</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.666667</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.888889</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5pmmig</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.906155</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.320888</td>\n",
-       "      <td>1.310784</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.800000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e64l6vq</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>1.242453</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e6fjx0d</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>1.945910</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.945910</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>1.039721</td>\n",
-       "      <td>0.682908</td>\n",
-       "      <td>0.964963</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>3.500000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.333333</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.750000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5h3xyy</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.888889</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e589ri5</th>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.002718</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.002718</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.002718</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>2.197225</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.250000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5beuqa</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.153742</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.475076</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.475076</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.475076</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.475076</td>\n",
-       "      <td>1.427061</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.800000</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.833333</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5lqoj1</th>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.098612</td>\n",
-       "      <td>1.073543</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.303092</td>\n",
-       "      <td>1.386294</td>\n",
-       "      <td>1.303092</td>\n",
-       "      <td>0.636514</td>\n",
-       "      <td>1.667462</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>1.676988</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.571429</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.857143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5kvch1</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.332179</td>\n",
-       "      <td>1.494175</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>1.831020</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>1.831020</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>1.732868</td>\n",
-       "      <td>1.560710</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.250000</td>\n",
-       "      <td>1.600000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.333333</td>\n",
-       "      <td>1.200000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>1.142857</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.285714</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.375000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.333333</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.714286</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>0.857143</td>\n",
-       "      <td>0.833333</td>\n",
-       "      <td>0.857143</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>e6srvwm</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <th>...</th>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>e65ca8k</th>\n",
        "      <td>2.0</td>\n",
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        "      <td>1.0</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>1.000000</td>\n",
+       "      <td>0.111111</td>\n",
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        "      <td>0.500000</td>\n",
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        "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
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-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
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-       "      <td>1.0</td>\n",
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-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
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-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
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        "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.329661</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.791759</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.0</td>\n",
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        "      <td>0.0</td>\n",
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        "      <td>1.0</td>\n",
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-       "      <td>1.000000</td>\n",
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        "      <td>0.111111</td>\n",
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        "      <td>0.111111</td>\n",
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-       "      <td>0.333333</td>\n",
-       "      <td>0.333333</td>\n",
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-       "      <td>0.222222</td>\n",
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-       "      <td>0.600000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.600000</td>\n",
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        "      <td>0.500000</td>\n",
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        "      <td>0.125000</td>\n",
-       "      <td>0.000000</td>\n",
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        "      <td>0.125000</td>\n",
        "      <td>0.500000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.444444</td>\n",
-       "      <td>0.5</td>\n",
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-       "      <td>0.5</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.888889</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>0.888889</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e5o65mk</th>\n",
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        "      <td>1.0</td>\n",
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        "      <td>1.0</td>\n",
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        "      <td>1.000000</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>1.000000</td>\n",
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        "      <td>1.000000</td>\n",
        "      <td>0.500000</td>\n",
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        "      <td>1.000000</td>\n",
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-       "      <td>1.0</td>\n",
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-       "      <td>1.0</td>\n",
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-       "      <td>3.0</td>\n",
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        "      <td>1.0</td>\n",
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-       "      <td>7.0</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>1.945910</td>\n",
-       "      <td>2.079442</td>\n",
-       "      <td>1.945910</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.693147</td>\n",
-       "      <td>0.682908</td>\n",
-       "      <td>0.693147</td>\n",
        "      <td>1.0</td>\n",
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-       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
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        "      <td>1.0</td>\n",
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-       "      <td>1.000000</td>\n",
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-       "      <td>1.000000</td>\n",
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        "      <td>3.500000</td>\n",
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-       "      <td>1.000000</td>\n",
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-       "      <td>0.8</td>\n",
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-       "      <td>0.500000</td>\n",
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-       "      <td>0.111111</td>\n",
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-       "      <td>0.500000</td>\n",
-       "      <td>0.428571</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
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-       "      <td>0.142857</td>\n",
-       "      <td>0.222222</td>\n",
        "      <td>0.500000</td>\n",
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-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>0.777778</td>\n",
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-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
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+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>e647cm8</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
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        "      <td>1.0</td>\n",
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-       "      <td>1.0</td>\n",
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        "      <td>1.0</td>\n",
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        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
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        "      <td>0.0</td>\n",
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-       "      <td>1.0</td>\n",
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-       "      <td>0.0</td>\n",
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-       "      <td>1.214890</td>\n",
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-       "      <td>1.214890</td>\n",
-       "      <td>0.950271</td>\n",
-       "      <td>1.214890</td>\n",
-       "      <td>1.609438</td>\n",
-       "      <td>2.197225</td>\n",
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        "      <td>1.609438</td>\n",
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        "      <td>1.0</td>\n",
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        "      <td>1.0</td>\n",
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-       "      <td>0.333333</td>\n",
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-       "      <td>0.555556</td>\n",
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-       "    <tr>\n",
-       "      <th>e58n526</th>\n",
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-       "      <td>NaN</td>\n",
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-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
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-       "      <td>NaN</td>\n",
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-       "      <td>9.000000</td>\n",
-       "      <td>0.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.125000</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>4.000000</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
+       "      <td>0.888889</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>0.000000</td>\n",
+       "      <td>0.693147</td>\n",
+       "      <td>2.079442</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>1.000000</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.000000</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.000000</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.100000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.1</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.1</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.900000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.900000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>e69r2kg</th>\n",
+       "      <td>0.693147</td>\n",
+       "      <td>0.693147</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>7.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>e6ua0sb</th>\n",
+       "      <td>4.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.444444</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.800000</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>1.427061</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.444444</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>0.666667</td>\n",
-       "      <td>1.000000</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>1.800000</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.800000</td>\n",
+       "      <td>1.800000</td>\n",
        "      <td>1.000000</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>1.522955</td>\n",
+       "      <td>1.427061</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>1.750000</td>\n",
        "      <td>1.000000</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.549826</td>\n",
+       "      <td>1.153742</td>\n",
        "      <td>1.000000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.500000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>0.777778</td>\n",
+       "      <td>1.750000</td>\n",
+       "      <td>0.444444</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.153742</td>\n",
+       "      <td>0.250000</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.571429</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>0.777778</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>1.750000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.444444</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.549826</td>\n",
+       "      <td>1.153742</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.250000</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.142857</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>1.400000</td>\n",
+       "      <td>1.750000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.549826</td>\n",
+       "      <td>1.153742</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.250000</td>\n",
        "      <td>1.0</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
        "      <td>4.0</td>\n",
-       "      <td>5.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>6.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>1.277034</td>\n",
-       "      <td>1.522955</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.549826</td>\n",
-       "      <td>1.735126</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>2.043192</td>\n",
-       "      <td>1.747868</td>\n",
-       "      <td>2.043192</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>e5ua84v</th>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.500000</td>\n",
+       "      <td>0.6</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1.676988</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>0.9</td>\n",
+       "      <td>1.500000</td>\n",
+       "      <td>1.500000</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.6</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1.676988</td>\n",
+       "      <td>1.676988</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.444444</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>0.222222</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>1.285714</td>\n",
+       "      <td>1.500000</td>\n",
+       "      <td>1.800000</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>1.676988</td>\n",
+       "      <td>1.427061</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.500000</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>5.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>7.0</td>\n",
        "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.375000</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>0.555556</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>1.494175</td>\n",
+       "      <td>0.666667</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.375000</td>\n",
        "      <td>2.0</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>0.888889</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>1.600000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.555556</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>1.732868</td>\n",
+       "      <td>1.494175</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.666667</td>\n",
        "      <td>2.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.500000</td>\n",
        "      <td>2.0</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>1.750000</td>\n",
-       "      <td>1.800000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.400000</td>\n",
-       "      <td>1.500000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>1.166667</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.777778</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.875000</td>\n",
-       "      <td>1.125000</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.142857</td>\n",
-       "      <td>0.111111</td>\n",
-       "      <td>0.428571</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.666667</td>\n",
        "      <td>0.333333</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.285714</td>\n",
-       "      <td>0.222222</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.600000</td>\n",
-       "      <td>0.400000</td>\n",
-       "      <td>0.500000</td>\n",
-       "      <td>0.400000</td>\n",
        "      <td>0.500000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.125000</td>\n",
-       "      <td>0.166667</td>\n",
-       "      <td>0.125000</td>\n",
+       "      <td>1.732868</td>\n",
+       "      <td>1.213008</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.500000</td>\n",
-       "      <td>0.625000</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.555556</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>0.750000</td>\n",
-       "      <td>1.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -10114,8641 +2959,1778 @@
        "</div>"
       ],
       "text/plain": [
-       "         2nd-argmax[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                0.0     \n",
-       "e5ywqyk                                                1.0     \n",
-       "e5qv9rj                                                0.0     \n",
-       "e6jhojf                                                0.0     \n",
-       "e6989ii                                                1.0     \n",
-       "e69lgse                                                2.0     \n",
-       "e5kwkg2                                                1.0     \n",
-       "e6mehe7                                                0.0     \n",
-       "e6m0hsd                                                1.0     \n",
-       "e64r385                                                3.0     \n",
-       "e5surbt                                                1.0     \n",
-       "e58gxii                                                4.0     \n",
-       "e64vc8y                                                2.0     \n",
-       "e57504g                                                1.0     \n",
-       "e5borjq                                                0.0     \n",
-       "e64n9zv                                                1.0     \n",
-       "e582ud3                                                5.0     \n",
-       "e64i9cf                                                0.0     \n",
-       "e6q9204                                                1.0     \n",
-       "e5modd7                                                0.0     \n",
-       "e5xhbyd                                                1.0     \n",
-       "e5oaf7h                                                1.0     \n",
-       "e6nir3u                                                1.0     \n",
-       "e6c3xdn                                                2.0     \n",
-       "e5d3zaa                                                1.0     \n",
-       "e5gnjv9                                                0.0     \n",
-       "e69gw2t                                                2.0     \n",
-       "e5syrih                                                1.0     \n",
-       "e5sa2yf                                                1.0     \n",
-       "e6ai7z5                                                1.0     \n",
-       "...                                                    ...     \n",
-       "e5smhzk                                                1.0     \n",
-       "e5v91s0                                                0.0     \n",
-       "e6n6di6                                                0.0     \n",
-       "e6iqq30                                                1.0     \n",
-       "e5bfad7                                                1.0     \n",
-       "e6x5he5                                                2.0     \n",
-       "e6l9uyf                                                0.0     \n",
-       "e57hyr1                                                1.0     \n",
-       "e5b8sj7                                                1.0     \n",
-       "e6nlep7                                                1.0     \n",
-       "e6ltazd                                                4.0     \n",
-       "e57a6qq                                                1.0     \n",
-       "e5qc7eb                                                2.0     \n",
-       "e6hqt5y                                                2.0     \n",
-       "e5ua84v                                                3.0     \n",
-       "e65m7kq                                                2.0     \n",
-       "e5ggtru                                                3.0     \n",
-       "e5pmmig                                                2.0     \n",
-       "e64l6vq                                                0.0     \n",
-       "e6fjx0d                                                1.0     \n",
-       "e5h3xyy                                                0.0     \n",
-       "e589ri5                                                4.0     \n",
-       "e5beuqa                                                0.0     \n",
-       "e5lqoj1                                                4.0     \n",
-       "e5kvch1                                                1.0     \n",
-       "e6srvwm                                                2.0     \n",
-       "e5o65mk                                                1.0     \n",
-       "e647cm8                                                1.0     \n",
-       "e58n526                                                1.0     \n",
-       "e69r2kg                                                0.0     \n",
-       "\n",
-       "         2nd-argmax[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                       1.0   \n",
-       "e5ywqyk                                       1.0   \n",
-       "e5qv9rj                                       3.0   \n",
-       "e6jhojf                                       1.0   \n",
-       "e6989ii                                       1.0   \n",
-       "e69lgse                                       2.0   \n",
-       "e5kwkg2                                       1.0   \n",
-       "e6mehe7                                       2.0   \n",
-       "e6m0hsd                                       0.0   \n",
-       "e64r385                                       2.0   \n",
-       "e5surbt                                       1.0   \n",
-       "e58gxii                                       4.0   \n",
-       "e64vc8y                                       1.0   \n",
-       "e57504g                                       1.0   \n",
-       "e5borjq                                       0.0   \n",
-       "e64n9zv                                       0.0   \n",
-       "e582ud3                                       1.0   \n",
-       "e64i9cf                                       2.0   \n",
-       "e6q9204                                       2.0   \n",
-       "e5modd7                                       1.0   \n",
-       "e5xhbyd                                       1.0   \n",
-       "e5oaf7h                                       0.0   \n",
-       "e6nir3u                                       1.0   \n",
-       "e6c3xdn                                       0.0   \n",
-       "e5d3zaa                                       1.0   \n",
-       "e5gnjv9                                       3.0   \n",
-       "e69gw2t                                       1.0   \n",
-       "e5syrih                                       2.0   \n",
-       "e5sa2yf                                       1.0   \n",
-       "e6ai7z5                                       1.0   \n",
-       "...                                           ...   \n",
-       "e5smhzk                                       1.0   \n",
-       "e5v91s0                                       2.0   \n",
-       "e6n6di6                                       1.0   \n",
-       "e6iqq30                                       1.0   \n",
-       "e5bfad7                                       1.0   \n",
-       "e6x5he5                                       1.0   \n",
-       "e6l9uyf                                       3.0   \n",
-       "e57hyr1                                       5.0   \n",
-       "e5b8sj7                                       0.0   \n",
-       "e6nlep7                                       1.0   \n",
-       "e6ltazd                                       0.0   \n",
-       "e57a6qq                                       0.0   \n",
-       "e5qc7eb                                       2.0   \n",
-       "e6hqt5y                                       1.0   \n",
-       "e5ua84v                                       4.0   \n",
-       "e65m7kq                                       2.0   \n",
-       "e5ggtru                                       4.0   \n",
-       "e5pmmig                                       3.0   \n",
-       "e64l6vq                                       2.0   \n",
-       "e6fjx0d                                       1.0   \n",
-       "e5h3xyy                                       5.0   \n",
-       "e589ri5                                       2.0   \n",
-       "e5beuqa                                       0.0   \n",
-       "e5lqoj1                                       1.0   \n",
-       "e5kvch1                                       4.0   \n",
-       "e6srvwm                                       1.0   \n",
-       "e5o65mk                                       1.0   \n",
-       "e647cm8                                       1.0   \n",
-       "e58n526                                       1.0   \n",
-       "e69r2kg                                       0.0   \n",
+       "         max[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                3.0   \n",
+       "e5ytz1d                                3.0   \n",
+       "e6ls80j                                4.0   \n",
+       "e5mhgl5                                2.0   \n",
+       "e6w6fah                                9.0   \n",
+       "...                                    ...   \n",
+       "e65ca8k                                2.0   \n",
+       "e6cdkpy                                4.0   \n",
+       "e5wc4tj                                1.0   \n",
+       "e6ua0sb                                4.0   \n",
+       "e5ua84v                                3.0   \n",
        "\n",
-       "         2nd-argmax[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0     \n",
-       "e5ywqyk                                                1.0     \n",
-       "e5qv9rj                                                0.0     \n",
-       "e6jhojf                                                0.0     \n",
-       "e6989ii                                                1.0     \n",
-       "e69lgse                                                2.0     \n",
-       "e5kwkg2                                                1.0     \n",
-       "e6mehe7                                                0.0     \n",
-       "e6m0hsd                                                1.0     \n",
-       "e64r385                                                3.0     \n",
-       "e5surbt                                                1.0     \n",
-       "e58gxii                                                6.0     \n",
-       "e64vc8y                                                2.0     \n",
-       "e57504g                                                1.0     \n",
-       "e5borjq                                                0.0     \n",
-       "e64n9zv                                                0.0     \n",
-       "e582ud3                                                5.0     \n",
-       "e64i9cf                                                0.0     \n",
-       "e6q9204                                                1.0     \n",
-       "e5modd7                                                0.0     \n",
-       "e5xhbyd                                                1.0     \n",
-       "e5oaf7h                                                2.0     \n",
-       "e6nir3u                                                1.0     \n",
-       "e6c3xdn                                                2.0     \n",
-       "e5d3zaa                                                1.0     \n",
-       "e5gnjv9                                                0.0     \n",
-       "e69gw2t                                                4.0     \n",
-       "e5syrih                                                1.0     \n",
-       "e5sa2yf                                                1.0     \n",
-       "e6ai7z5                                                1.0     \n",
-       "...                                                    ...     \n",
-       "e5smhzk                                                2.0     \n",
-       "e5v91s0                                                0.0     \n",
-       "e6n6di6                                                0.0     \n",
-       "e6iqq30                                                1.0     \n",
-       "e5bfad7                                                1.0     \n",
-       "e6x5he5                                                2.0     \n",
-       "e6l9uyf                                                0.0     \n",
-       "e57hyr1                                                1.0     \n",
-       "e5b8sj7                                                1.0     \n",
-       "e6nlep7                                                1.0     \n",
-       "e6ltazd                                                4.0     \n",
-       "e57a6qq                                                4.0     \n",
-       "e5qc7eb                                                2.0     \n",
-       "e6hqt5y                                                2.0     \n",
-       "e5ua84v                                                4.0     \n",
-       "e65m7kq                                                2.0     \n",
-       "e5ggtru                                                4.0     \n",
-       "e5pmmig                                                1.0     \n",
-       "e64l6vq                                                0.0     \n",
-       "e6fjx0d                                                1.0     \n",
-       "e5h3xyy                                                0.0     \n",
-       "e589ri5                                                4.0     \n",
-       "e5beuqa                                                2.0     \n",
-       "e5lqoj1                                                4.0     \n",
-       "e5kvch1                                                2.0     \n",
-       "e6srvwm                                                2.0     \n",
-       "e5o65mk                                                1.0     \n",
-       "e647cm8                                                1.0     \n",
-       "e58n526                                                1.0     \n",
-       "e69r2kg                                                4.0     \n",
+       "         argmax[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                   1.0   \n",
+       "e5ytz1d                                   0.0   \n",
+       "e6ls80j                                   0.0   \n",
+       "e5mhgl5                                   1.0   \n",
+       "e6w6fah                                   0.0   \n",
+       "...                                       ...   \n",
+       "e65ca8k                                   0.0   \n",
+       "e6cdkpy                                   0.0   \n",
+       "e5wc4tj                                   0.0   \n",
+       "e6ua0sb                                   2.0   \n",
+       "e5ua84v                                   1.0   \n",
        "\n",
-       "         2nd-argmax[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                       1.0   \n",
-       "e5ywqyk                                       0.0   \n",
-       "e5qv9rj                                       3.0   \n",
-       "e6jhojf                                       0.0   \n",
-       "e6989ii                                       1.0   \n",
-       "e69lgse                                       2.0   \n",
-       "e5kwkg2                                       1.0   \n",
-       "e6mehe7                                       2.0   \n",
-       "e6m0hsd                                       0.0   \n",
-       "e64r385                                       2.0   \n",
-       "e5surbt                                       1.0   \n",
-       "e58gxii                                       2.0   \n",
-       "e64vc8y                                       1.0   \n",
-       "e57504g                                       1.0   \n",
-       "e5borjq                                       0.0   \n",
-       "e64n9zv                                       0.0   \n",
-       "e582ud3                                       1.0   \n",
-       "e64i9cf                                       3.0   \n",
-       "e6q9204                                       2.0   \n",
-       "e5modd7                                       1.0   \n",
-       "e5xhbyd                                       2.0   \n",
-       "e5oaf7h                                       3.0   \n",
-       "e6nir3u                                       1.0   \n",
-       "e6c3xdn                                       0.0   \n",
-       "e5d3zaa                                       1.0   \n",
-       "e5gnjv9                                       3.0   \n",
-       "e69gw2t                                       1.0   \n",
-       "e5syrih                                       2.0   \n",
-       "e5sa2yf                                       1.0   \n",
-       "e6ai7z5                                       1.0   \n",
-       "...                                           ...   \n",
-       "e5smhzk                                       1.0   \n",
-       "e5v91s0                                       2.0   \n",
-       "e6n6di6                                       1.0   \n",
-       "e6iqq30                                       1.0   \n",
-       "e5bfad7                                       1.0   \n",
-       "e6x5he5                                       1.0   \n",
-       "e6l9uyf                                       4.0   \n",
-       "e57hyr1                                       5.0   \n",
-       "e5b8sj7                                       1.0   \n",
-       "e6nlep7                                       1.0   \n",
-       "e6ltazd                                       0.0   \n",
-       "e57a6qq                                       5.0   \n",
-       "e5qc7eb                                       0.0   \n",
-       "e6hqt5y                                       1.0   \n",
-       "e5ua84v                                       5.0   \n",
-       "e65m7kq                                       2.0   \n",
-       "e5ggtru                                       5.0   \n",
-       "e5pmmig                                       0.0   \n",
-       "e64l6vq                                       5.0   \n",
-       "e6fjx0d                                       1.0   \n",
-       "e5h3xyy                                       5.0   \n",
-       "e589ri5                                       2.0   \n",
-       "e5beuqa                                       0.0   \n",
-       "e5lqoj1                                       1.0   \n",
-       "e5kvch1                                       2.0   \n",
-       "e6srvwm                                       1.0   \n",
-       "e5o65mk                                       1.0   \n",
-       "e647cm8                                       1.0   \n",
-       "e58n526                                       1.0   \n",
-       "e69r2kg                                       1.0   \n",
+       "         norm.max[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                0.333333   \n",
+       "e5ytz1d                                0.333333   \n",
+       "e6ls80j                                0.444444   \n",
+       "e5mhgl5                                0.222222   \n",
+       "e6w6fah                                1.000000   \n",
+       "...                                         ...   \n",
+       "e65ca8k                                0.222222   \n",
+       "e6cdkpy                                0.444444   \n",
+       "e5wc4tj                                0.111111   \n",
+       "e6ua0sb                                0.444444   \n",
+       "e5ua84v                                0.333333   \n",
        "\n",
-       "         2nd-argmax[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0     \n",
-       "e5ywqyk                                                1.0     \n",
-       "e5qv9rj                                                0.0     \n",
-       "e6jhojf                                                0.0     \n",
-       "e6989ii                                                0.0     \n",
-       "e69lgse                                                2.0     \n",
-       "e5kwkg2                                                1.0     \n",
-       "e6mehe7                                                0.0     \n",
-       "e6m0hsd                                                1.0     \n",
-       "e64r385                                                3.0     \n",
-       "e5surbt                                                1.0     \n",
-       "e58gxii                                                6.0     \n",
-       "e64vc8y                                                2.0     \n",
-       "e57504g                                                1.0     \n",
-       "e5borjq                                                0.0     \n",
-       "e64n9zv                                                0.0     \n",
-       "e582ud3                                                5.0     \n",
-       "e64i9cf                                                0.0     \n",
-       "e6q9204                                                1.0     \n",
-       "e5modd7                                                0.0     \n",
-       "e5xhbyd                                                1.0     \n",
-       "e5oaf7h                                                2.0     \n",
-       "e6nir3u                                                0.0     \n",
-       "e6c3xdn                                                2.0     \n",
-       "e5d3zaa                                                1.0     \n",
-       "e5gnjv9                                                0.0     \n",
-       "e69gw2t                                                4.0     \n",
-       "e5syrih                                                1.0     \n",
-       "e5sa2yf                                                1.0     \n",
-       "e6ai7z5                                                1.0     \n",
-       "...                                                    ...     \n",
-       "e5smhzk                                                2.0     \n",
-       "e5v91s0                                                0.0     \n",
-       "e6n6di6                                                0.0     \n",
-       "e6iqq30                                                1.0     \n",
-       "e5bfad7                                                1.0     \n",
-       "e6x5he5                                                0.0     \n",
-       "e6l9uyf                                                0.0     \n",
-       "e57hyr1                                                1.0     \n",
-       "e5b8sj7                                                1.0     \n",
-       "e6nlep7                                                1.0     \n",
-       "e6ltazd                                                4.0     \n",
-       "e57a6qq                                                4.0     \n",
-       "e5qc7eb                                                2.0     \n",
-       "e6hqt5y                                                2.0     \n",
-       "e5ua84v                                                4.0     \n",
-       "e65m7kq                                                2.0     \n",
-       "e5ggtru                                                4.0     \n",
-       "e5pmmig                                                1.0     \n",
-       "e64l6vq                                                0.0     \n",
-       "e6fjx0d                                                1.0     \n",
-       "e5h3xyy                                                0.0     \n",
-       "e589ri5                                                4.0     \n",
-       "e5beuqa                                                2.0     \n",
-       "e5lqoj1                                                4.0     \n",
-       "e5kvch1                                                2.0     \n",
-       "e6srvwm                                                2.0     \n",
-       "e5o65mk                                                1.0     \n",
-       "e647cm8                                                1.0     \n",
-       "e58n526                                                1.0     \n",
-       "e69r2kg                                                4.0     \n",
+       "         2nd-largest[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                        1.0   \n",
+       "e5ytz1d                                        3.0   \n",
+       "e6ls80j                                        3.0   \n",
+       "e5mhgl5                                        2.0   \n",
+       "e6w6fah                                        0.0   \n",
+       "...                                            ...   \n",
+       "e65ca8k                                        1.0   \n",
+       "e6cdkpy                                        2.0   \n",
+       "e5wc4tj                                        1.0   \n",
+       "e6ua0sb                                        2.0   \n",
+       "e5ua84v                                        2.0   \n",
        "\n",
        "         2nd-argmax[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                       1.0   \n",
-       "e5ywqyk                                       0.0   \n",
-       "e5qv9rj                                       3.0   \n",
-       "e6jhojf                                       0.0   \n",
-       "e6989ii                                       0.0   \n",
-       "e69lgse                                       2.0   \n",
-       "e5kwkg2                                       1.0   \n",
-       "e6mehe7                                       2.0   \n",
-       "e6m0hsd                                       0.0   \n",
-       "e64r385                                       2.0   \n",
-       "e5surbt                                       1.0   \n",
-       "e58gxii                                       2.0   \n",
-       "e64vc8y                                       1.0   \n",
-       "e57504g                                       1.0   \n",
-       "e5borjq                                       0.0   \n",
-       "e64n9zv                                       0.0   \n",
-       "e582ud3                                       1.0   \n",
-       "e64i9cf                                       3.0   \n",
-       "e6q9204                                       2.0   \n",
-       "e5modd7                                       1.0   \n",
-       "e5xhbyd                                       2.0   \n",
-       "e5oaf7h                                       3.0   \n",
-       "e6nir3u                                       0.0   \n",
-       "e6c3xdn                                       0.0   \n",
-       "e5d3zaa                                       1.0   \n",
-       "e5gnjv9                                       3.0   \n",
-       "e69gw2t                                       1.0   \n",
-       "e5syrih                                       2.0   \n",
-       "e5sa2yf                                       1.0   \n",
-       "e6ai7z5                                       1.0   \n",
+       "e5hm9mp                                       0.0   \n",
+       "e5ytz1d                                       2.0   \n",
+       "e6ls80j                                       2.0   \n",
+       "e5mhgl5                                       4.0   \n",
+       "e6w6fah                                       1.0   \n",
        "...                                           ...   \n",
-       "e5smhzk                                       1.0   \n",
-       "e5v91s0                                       2.0   \n",
-       "e6n6di6                                       1.0   \n",
-       "e6iqq30                                       1.0   \n",
-       "e5bfad7                                       1.0   \n",
-       "e6x5he5                                       4.0   \n",
-       "e6l9uyf                                       4.0   \n",
-       "e57hyr1                                       5.0   \n",
-       "e5b8sj7                                       1.0   \n",
-       "e6nlep7                                       1.0   \n",
-       "e6ltazd                                       0.0   \n",
-       "e57a6qq                                       5.0   \n",
-       "e5qc7eb                                       0.0   \n",
-       "e6hqt5y                                       1.0   \n",
+       "e65ca8k                                       2.0   \n",
+       "e6cdkpy                                       1.0   \n",
+       "e5wc4tj                                       1.0   \n",
+       "e6ua0sb                                       0.0   \n",
        "e5ua84v                                       5.0   \n",
-       "e65m7kq                                       2.0   \n",
-       "e5ggtru                                       5.0   \n",
-       "e5pmmig                                       0.0   \n",
-       "e64l6vq                                       5.0   \n",
-       "e6fjx0d                                       1.0   \n",
-       "e5h3xyy                                       5.0   \n",
-       "e589ri5                                       2.0   \n",
-       "e5beuqa                                       0.0   \n",
-       "e5lqoj1                                       1.0   \n",
-       "e5kvch1                                       2.0   \n",
-       "e6srvwm                                       1.0   \n",
-       "e5o65mk                                       1.0   \n",
-       "e647cm8                                       1.0   \n",
-       "e58n526                                       1.0   \n",
-       "e69r2kg                                       1.0   \n",
-       "\n",
-       "         2nd-argmax[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                2.0      \n",
-       "e5ywqyk                                                2.0      \n",
-       "e5qv9rj                                                3.0      \n",
-       "e6jhojf                                                2.0      \n",
-       "e6989ii                                                1.0      \n",
-       "e69lgse                                                1.0      \n",
-       "e5kwkg2                                                2.0      \n",
-       "e6mehe7                                                3.0      \n",
-       "e6m0hsd                                                1.0      \n",
-       "e64r385                                                1.0      \n",
-       "e5surbt                                                3.0      \n",
-       "e58gxii                                                0.0      \n",
-       "e64vc8y                                                6.0      \n",
-       "e57504g                                                1.0      \n",
-       "e5borjq                                                2.0      \n",
-       "e64n9zv                                                1.0      \n",
-       "e582ud3                                                6.0      \n",
-       "e64i9cf                                                2.0      \n",
-       "e6q9204                                                1.0      \n",
-       "e5modd7                                                2.0      \n",
-       "e5xhbyd                                                1.0      \n",
-       "e5oaf7h                                                1.0      \n",
-       "e6nir3u                                                1.0      \n",
-       "e6c3xdn                                                2.0      \n",
-       "e5d3zaa                                                1.0      \n",
-       "e5gnjv9                                                0.0      \n",
-       "e69gw2t                                                0.0      \n",
-       "e5syrih                                                0.0      \n",
-       "e5sa2yf                                                1.0      \n",
-       "e6ai7z5                                                3.0      \n",
-       "...                                                    ...      \n",
-       "e5smhzk                                                2.0      \n",
-       "e5v91s0                                                4.0      \n",
-       "e6n6di6                                                2.0      \n",
-       "e6iqq30                                                5.0      \n",
-       "e5bfad7                                                1.0      \n",
-       "e6x5he5                                                0.0      \n",
-       "e6l9uyf                                                4.0      \n",
-       "e57hyr1                                                2.0      \n",
-       "e5b8sj7                                                1.0      \n",
-       "e6nlep7                                                1.0      \n",
-       "e6ltazd                                                1.0      \n",
-       "e57a6qq                                                0.0      \n",
-       "e5qc7eb                                                1.0      \n",
-       "e6hqt5y                                                3.0      \n",
-       "e5ua84v                                                3.0      \n",
-       "e65m7kq                                                2.0      \n",
-       "e5ggtru                                                1.0      \n",
-       "e5pmmig                                                2.0      \n",
-       "e64l6vq                                                0.0      \n",
-       "e6fjx0d                                                1.0      \n",
-       "e5h3xyy                                                4.0      \n",
-       "e589ri5                                                6.0      \n",
-       "e5beuqa                                                0.0      \n",
-       "e5lqoj1                                                5.0      \n",
-       "e5kvch1                                                2.0      \n",
-       "e6srvwm                                                1.0      \n",
-       "e5o65mk                                                1.0      \n",
-       "e647cm8                                                2.0      \n",
-       "e58n526                                                1.0      \n",
-       "e69r2kg                                                1.0      \n",
-       "\n",
-       "         2nd-argmax[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                        1.0   \n",
-       "e5ywqyk                                        1.0   \n",
-       "e5qv9rj                                        2.0   \n",
-       "e6jhojf                                        1.0   \n",
-       "e6989ii                                        1.0   \n",
-       "e69lgse                                        1.0   \n",
-       "e5kwkg2                                        2.0   \n",
-       "e6mehe7                                        1.0   \n",
-       "e6m0hsd                                        0.0   \n",
-       "e64r385                                        3.0   \n",
-       "e5surbt                                        2.0   \n",
-       "e58gxii                                        1.0   \n",
-       "e64vc8y                                        2.0   \n",
-       "e57504g                                        6.0   \n",
-       "e5borjq                                        0.0   \n",
-       "e64n9zv                                        0.0   \n",
-       "e582ud3                                        2.0   \n",
-       "e64i9cf                                        1.0   \n",
-       "e6q9204                                        2.0   \n",
-       "e5modd7                                        2.0   \n",
-       "e5xhbyd                                        1.0   \n",
-       "e5oaf7h                                        0.0   \n",
-       "e6nir3u                                        1.0   \n",
-       "e6c3xdn                                        2.0   \n",
-       "e5d3zaa                                        2.0   \n",
-       "e5gnjv9                                        1.0   \n",
-       "e69gw2t                                        2.0   \n",
-       "e5syrih                                        3.0   \n",
-       "e5sa2yf                                        1.0   \n",
-       "e6ai7z5                                        0.0   \n",
-       "...                                            ...   \n",
-       "e5smhzk                                        1.0   \n",
-       "e5v91s0                                        2.0   \n",
-       "e6n6di6                                        1.0   \n",
-       "e6iqq30                                        1.0   \n",
-       "e5bfad7                                        1.0   \n",
-       "e6x5he5                                        1.0   \n",
-       "e6l9uyf                                        1.0   \n",
-       "e57hyr1                                        3.0   \n",
-       "e5b8sj7                                        0.0   \n",
-       "e6nlep7                                        2.0   \n",
-       "e6ltazd                                        2.0   \n",
-       "e57a6qq                                        1.0   \n",
-       "e5qc7eb                                        0.0   \n",
-       "e6hqt5y                                        1.0   \n",
-       "e5ua84v                                        4.0   \n",
-       "e65m7kq                                        1.0   \n",
-       "e5ggtru                                        2.0   \n",
-       "e5pmmig                                        3.0   \n",
-       "e64l6vq                                        1.0   \n",
-       "e6fjx0d                                        2.0   \n",
-       "e5h3xyy                                        1.0   \n",
-       "e589ri5                                        2.0   \n",
-       "e5beuqa                                        1.0   \n",
-       "e5lqoj1                                        1.0   \n",
-       "e5kvch1                                        4.0   \n",
-       "e6srvwm                                        2.0   \n",
-       "e5o65mk                                        1.0   \n",
-       "e647cm8                                        1.0   \n",
-       "e58n526                                        2.0   \n",
-       "e69r2kg                                        0.0   \n",
-       "\n",
-       "         2nd-argmax[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                2.0      \n",
-       "e5ywqyk                                                3.0      \n",
-       "e5qv9rj                                                3.0      \n",
-       "e6jhojf                                                2.0      \n",
-       "e6989ii                                                0.0      \n",
-       "e69lgse                                                1.0      \n",
-       "e5kwkg2                                                2.0      \n",
-       "e6mehe7                                                3.0      \n",
-       "e6m0hsd                                                1.0      \n",
-       "e64r385                                                1.0      \n",
-       "e5surbt                                                3.0      \n",
-       "e58gxii                                                0.0      \n",
-       "e64vc8y                                                6.0      \n",
-       "e57504g                                                1.0      \n",
-       "e5borjq                                                2.0      \n",
-       "e64n9zv                                                2.0      \n",
-       "e582ud3                                                6.0      \n",
-       "e64i9cf                                                2.0      \n",
-       "e6q9204                                                2.0      \n",
-       "e5modd7                                                2.0      \n",
-       "e5xhbyd                                                0.0      \n",
-       "e5oaf7h                                                1.0      \n",
-       "e6nir3u                                                0.0      \n",
-       "e6c3xdn                                                2.0      \n",
-       "e5d3zaa                                                1.0      \n",
-       "e5gnjv9                                                0.0      \n",
-       "e69gw2t                                                0.0      \n",
-       "e5syrih                                                0.0      \n",
-       "e5sa2yf                                                1.0      \n",
-       "e6ai7z5                                                3.0      \n",
-       "...                                                    ...      \n",
-       "e5smhzk                                                2.0      \n",
-       "e5v91s0                                                4.0      \n",
-       "e6n6di6                                                2.0      \n",
-       "e6iqq30                                                5.0      \n",
-       "e5bfad7                                                1.0      \n",
-       "e6x5he5                                                0.0      \n",
-       "e6l9uyf                                                4.0      \n",
-       "e57hyr1                                                2.0      \n",
-       "e5b8sj7                                                1.0      \n",
-       "e6nlep7                                                1.0      \n",
-       "e6ltazd                                                0.0      \n",
-       "e57a6qq                                                0.0      \n",
-       "e5qc7eb                                                0.0      \n",
-       "e6hqt5y                                                3.0      \n",
-       "e5ua84v                                                3.0      \n",
-       "e65m7kq                                                2.0      \n",
-       "e5ggtru                                                1.0      \n",
-       "e5pmmig                                                0.0      \n",
-       "e64l6vq                                                0.0      \n",
-       "e6fjx0d                                                0.0      \n",
-       "e5h3xyy                                                4.0      \n",
-       "e589ri5                                                6.0      \n",
-       "e5beuqa                                                0.0      \n",
-       "e5lqoj1                                                5.0      \n",
-       "e5kvch1                                                1.0      \n",
-       "e6srvwm                                                1.0      \n",
-       "e5o65mk                                                0.0      \n",
-       "e647cm8                                                2.0      \n",
-       "e58n526                                                1.0      \n",
-       "e69r2kg                                                1.0      \n",
        "\n",
-       "         2nd-argmax[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                        3.0   \n",
-       "e5ywqyk                                        3.0   \n",
-       "e5qv9rj                                        2.0   \n",
-       "e6jhojf                                        2.0   \n",
-       "e6989ii                                        1.0   \n",
-       "e69lgse                                        2.0   \n",
-       "e5kwkg2                                        2.0   \n",
-       "e6mehe7                                        3.0   \n",
-       "e6m0hsd                                        0.0   \n",
-       "e64r385                                        3.0   \n",
-       "e5surbt                                        2.0   \n",
-       "e58gxii                                        1.0   \n",
-       "e64vc8y                                        2.0   \n",
-       "e57504g                                        6.0   \n",
-       "e5borjq                                        0.0   \n",
-       "e64n9zv                                        2.0   \n",
-       "e582ud3                                        2.0   \n",
-       "e64i9cf                                        2.0   \n",
-       "e6q9204                                        3.0   \n",
-       "e5modd7                                        2.0   \n",
-       "e5xhbyd                                        1.0   \n",
-       "e5oaf7h                                        0.0   \n",
-       "e6nir3u                                        1.0   \n",
-       "e6c3xdn                                        2.0   \n",
-       "e5d3zaa                                        2.0   \n",
-       "e5gnjv9                                        1.0   \n",
-       "e69gw2t                                        2.0   \n",
-       "e5syrih                                        3.0   \n",
-       "e5sa2yf                                        0.0   \n",
-       "e6ai7z5                                        0.0   \n",
-       "...                                            ...   \n",
-       "e5smhzk                                        2.0   \n",
-       "e5v91s0                                        2.0   \n",
-       "e6n6di6                                        1.0   \n",
-       "e6iqq30                                        1.0   \n",
-       "e5bfad7                                        1.0   \n",
-       "e6x5he5                                        1.0   \n",
-       "e6l9uyf                                        1.0   \n",
-       "e57hyr1                                        3.0   \n",
-       "e5b8sj7                                        0.0   \n",
-       "e6nlep7                                        2.0   \n",
-       "e6ltazd                                        5.0   \n",
-       "e57a6qq                                        1.0   \n",
-       "e5qc7eb                                        1.0   \n",
-       "e6hqt5y                                        1.0   \n",
-       "e5ua84v                                        4.0   \n",
-       "e65m7kq                                        1.0   \n",
-       "e5ggtru                                        2.0   \n",
-       "e5pmmig                                        3.0   \n",
-       "e64l6vq                                        1.0   \n",
-       "e6fjx0d                                        2.0   \n",
-       "e5h3xyy                                        1.0   \n",
-       "e589ri5                                        2.0   \n",
-       "e5beuqa                                        1.0   \n",
-       "e5lqoj1                                        6.0   \n",
-       "e5kvch1                                        3.0   \n",
-       "e6srvwm                                        2.0   \n",
-       "e5o65mk                                        1.0   \n",
-       "e647cm8                                        1.0   \n",
-       "e58n526                                        2.0   \n",
-       "e69r2kg                                        0.0   \n",
+       "         norm.2nd-largest[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                        0.111111   \n",
+       "e5ytz1d                                        0.333333   \n",
+       "e6ls80j                                        0.333333   \n",
+       "e5mhgl5                                        0.222222   \n",
+       "e6w6fah                                        0.000000   \n",
+       "...                                                 ...   \n",
+       "e65ca8k                                        0.111111   \n",
+       "e6cdkpy                                        0.222222   \n",
+       "e5wc4tj                                        0.111111   \n",
+       "e6ua0sb                                        0.222222   \n",
+       "e5ua84v                                        0.222222   \n",
        "\n",
-       "         2nd-largest / max[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.333333            \n",
-       "e5ywqyk                                           0.500000            \n",
-       "e5qv9rj                                           0.333333            \n",
-       "e6jhojf                                           0.333333            \n",
-       "e6989ii                                           1.000000            \n",
-       "e69lgse                                           0.333333            \n",
-       "e5kwkg2                                           0.500000            \n",
-       "e6mehe7                                           0.500000            \n",
-       "e6m0hsd                                           0.500000            \n",
-       "e64r385                                           1.000000            \n",
-       "e5surbt                                           1.000000            \n",
-       "e58gxii                                           0.666667            \n",
-       "e64vc8y                                           1.000000            \n",
-       "e57504g                                           1.000000            \n",
-       "e5borjq                                           0.666667            \n",
-       "e64n9zv                                           0.500000            \n",
-       "e582ud3                                           0.500000            \n",
-       "e64i9cf                                           0.500000            \n",
-       "e6q9204                                           0.666667            \n",
-       "e5modd7                                           0.500000            \n",
-       "e5xhbyd                                           1.000000            \n",
-       "e5oaf7h                                           0.333333            \n",
-       "e6nir3u                                           1.000000            \n",
-       "e6c3xdn                                           0.500000            \n",
-       "e5d3zaa                                           1.000000            \n",
-       "e5gnjv9                                           0.000000            \n",
-       "e69gw2t                                           1.000000            \n",
-       "e5syrih                                           0.500000            \n",
-       "e5sa2yf                                           1.000000            \n",
-       "e6ai7z5                                           0.500000            \n",
-       "...                                                    ...            \n",
-       "e5smhzk                                           1.000000            \n",
-       "e5v91s0                                           0.500000            \n",
-       "e6n6di6                                           0.500000            \n",
-       "e6iqq30                                           1.000000            \n",
-       "e5bfad7                                           1.000000            \n",
-       "e6x5he5                                           1.000000            \n",
-       "e6l9uyf                                           0.500000            \n",
-       "e57hyr1                                           0.500000            \n",
-       "e5b8sj7                                           0.500000            \n",
-       "e6nlep7                                                NaN            \n",
-       "e6ltazd                                           0.250000            \n",
-       "e57a6qq                                           0.666667            \n",
-       "e5qc7eb                                           0.666667            \n",
-       "e6hqt5y                                           0.250000            \n",
-       "e5ua84v                                           0.500000            \n",
-       "e65m7kq                                           0.333333            \n",
-       "e5ggtru                                           0.400000            \n",
-       "e5pmmig                                           1.000000            \n",
-       "e64l6vq                                           0.500000            \n",
-       "e6fjx0d                                           1.000000            \n",
-       "e5h3xyy                                           0.500000            \n",
-       "e589ri5                                           1.000000            \n",
-       "e5beuqa                                           0.250000            \n",
-       "e5lqoj1                                           1.000000            \n",
-       "e5kvch1                                           0.500000            \n",
-       "e6srvwm                                           1.000000            \n",
-       "e5o65mk                                           1.000000            \n",
-       "e647cm8                                           0.333333            \n",
-       "e58n526                                                NaN            \n",
-       "e69r2kg                                           0.666667            \n",
+       "         mean[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                 0.9   \n",
+       "e5ytz1d                                 0.9   \n",
+       "e6ls80j                                 0.9   \n",
+       "e5mhgl5                                 0.9   \n",
+       "e6w6fah                                 0.9   \n",
+       "...                                     ...   \n",
+       "e65ca8k                                 0.9   \n",
+       "e6cdkpy                                 0.9   \n",
+       "e5wc4tj                                 0.9   \n",
+       "e6ua0sb                                 0.9   \n",
+       "e5ua84v                                 0.9   \n",
        "\n",
-       "         2nd-largest / max[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                         0.200000   \n",
-       "e5ywqyk                                         1.000000   \n",
-       "e5qv9rj                                         1.000000   \n",
-       "e6jhojf                                         0.250000   \n",
-       "e6989ii                                         1.000000   \n",
-       "e69lgse                                         1.000000   \n",
-       "e5kwkg2                                         0.666667   \n",
-       "e6mehe7                                         0.500000   \n",
-       "e6m0hsd                                         0.500000   \n",
-       "e64r385                                         1.000000   \n",
-       "e5surbt                                         0.200000   \n",
-       "e58gxii                                         0.500000   \n",
-       "e64vc8y                                         0.166667   \n",
-       "e57504g                                         1.000000   \n",
-       "e5borjq                                         0.666667   \n",
-       "e64n9zv                                         0.500000   \n",
-       "e582ud3                                         0.333333   \n",
-       "e64i9cf                                         0.500000   \n",
-       "e6q9204                                         0.666667   \n",
-       "e5modd7                                         0.500000   \n",
-       "e5xhbyd                                         1.000000   \n",
-       "e5oaf7h                                         0.333333   \n",
-       "e6nir3u                                         1.000000   \n",
-       "e6c3xdn                                         0.500000   \n",
-       "e5d3zaa                                         1.000000   \n",
-       "e5gnjv9                                         0.125000   \n",
-       "e69gw2t                                         1.000000   \n",
-       "e5syrih                                         0.500000   \n",
-       "e5sa2yf                                         1.000000   \n",
-       "e6ai7z5                                         0.666667   \n",
-       "...                                                  ...   \n",
-       "e5smhzk                                         0.500000   \n",
-       "e5v91s0                                         0.400000   \n",
-       "e6n6di6                                         0.500000   \n",
-       "e6iqq30                                         0.166667   \n",
-       "e5bfad7                                         0.500000   \n",
-       "e6x5he5                                         0.250000   \n",
-       "e6l9uyf                                         0.400000   \n",
-       "e57hyr1                                         0.500000   \n",
-       "e5b8sj7                                         0.750000   \n",
-       "e6nlep7                                         0.000000   \n",
-       "e6ltazd                                         0.250000   \n",
-       "e57a6qq                                         0.666667   \n",
-       "e5qc7eb                                         1.000000   \n",
-       "e6hqt5y                                         1.000000   \n",
-       "e5ua84v                                         0.500000   \n",
-       "e65m7kq                                         0.750000   \n",
-       "e5ggtru                                         0.400000   \n",
-       "e5pmmig                                         1.000000   \n",
-       "e64l6vq                                         0.666667   \n",
-       "e6fjx0d                                         0.500000   \n",
-       "e5h3xyy                                         0.500000   \n",
-       "e589ri5                                         0.166667   \n",
-       "e5beuqa                                         0.500000   \n",
-       "e5lqoj1                                         0.200000   \n",
-       "e5kvch1                                         0.666667   \n",
-       "e6srvwm                                         0.666667   \n",
-       "e5o65mk                                         1.000000   \n",
-       "e647cm8                                         0.750000   \n",
-       "e58n526                                         0.000000   \n",
-       "e69r2kg                                         0.666667   \n",
+       "         mean-nonzero[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                    1.285714   \n",
+       "e5ytz1d                                    2.250000   \n",
+       "e6ls80j                                    2.250000   \n",
+       "e5mhgl5                                    1.285714   \n",
+       "e6w6fah                                    9.000000   \n",
+       "...                                             ...   \n",
+       "e65ca8k                                    1.125000   \n",
+       "e6cdkpy                                    2.250000   \n",
+       "e5wc4tj                                    1.000000   \n",
+       "e6ua0sb                                    1.800000   \n",
+       "e5ua84v                                    1.500000   \n",
        "\n",
-       "         2nd-largest / max[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.000000            \n",
-       "e5ywqyk                                           0.500000            \n",
-       "e5qv9rj                                           0.333333            \n",
-       "e6jhojf                                           0.500000            \n",
-       "e6989ii                                           1.000000            \n",
-       "e69lgse                                           0.333333            \n",
-       "e5kwkg2                                           0.500000            \n",
-       "e6mehe7                                           0.500000            \n",
-       "e6m0hsd                                           0.500000            \n",
-       "e64r385                                           1.000000            \n",
-       "e5surbt                                           1.000000            \n",
-       "e58gxii                                           1.000000            \n",
-       "e64vc8y                                           1.000000            \n",
-       "e57504g                                           1.000000            \n",
-       "e5borjq                                           0.666667            \n",
-       "e64n9zv                                           0.500000            \n",
-       "e582ud3                                           0.500000            \n",
-       "e64i9cf                                           0.500000            \n",
-       "e6q9204                                           1.000000            \n",
-       "e5modd7                                           0.500000            \n",
-       "e5xhbyd                                           1.000000            \n",
-       "e5oaf7h                                           1.000000            \n",
-       "e6nir3u                                           1.000000            \n",
-       "e6c3xdn                                           0.500000            \n",
-       "e5d3zaa                                           1.000000            \n",
-       "e5gnjv9                                           0.000000            \n",
-       "e69gw2t                                           1.000000            \n",
-       "e5syrih                                           0.666667            \n",
-       "e5sa2yf                                           1.000000            \n",
-       "e6ai7z5                                           1.000000            \n",
-       "...                                                    ...            \n",
-       "e5smhzk                                           1.000000            \n",
-       "e5v91s0                                           0.500000            \n",
-       "e6n6di6                                           0.666667            \n",
-       "e6iqq30                                           1.000000            \n",
-       "e5bfad7                                           1.000000            \n",
-       "e6x5he5                                           1.000000            \n",
-       "e6l9uyf                                           0.500000            \n",
-       "e57hyr1                                           0.500000            \n",
-       "e5b8sj7                                           0.666667            \n",
-       "e6nlep7                                                NaN            \n",
-       "e6ltazd                                           0.250000            \n",
-       "e57a6qq                                           1.000000            \n",
-       "e5qc7eb                                           0.666667            \n",
-       "e6hqt5y                                           0.250000            \n",
-       "e5ua84v                                           0.666667            \n",
-       "e65m7kq                                           0.500000            \n",
-       "e5ggtru                                           0.500000            \n",
-       "e5pmmig                                           0.500000            \n",
-       "e64l6vq                                           0.500000            \n",
-       "e6fjx0d                                           1.000000            \n",
-       "e5h3xyy                                           0.500000            \n",
-       "e589ri5                                           1.000000            \n",
-       "e5beuqa                                           0.333333            \n",
-       "e5lqoj1                                           1.000000            \n",
-       "e5kvch1                                           1.000000            \n",
-       "e6srvwm                                           1.000000            \n",
-       "e5o65mk                                           1.000000            \n",
-       "e647cm8                                           0.333333            \n",
-       "e58n526                                                NaN            \n",
-       "e69r2kg                                           1.000000            \n",
+       "         prop-nonzero[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                         0.7   \n",
+       "e5ytz1d                                         0.4   \n",
+       "e6ls80j                                         0.4   \n",
+       "e5mhgl5                                         0.7   \n",
+       "e6w6fah                                         0.1   \n",
+       "...                                             ...   \n",
+       "e65ca8k                                         0.8   \n",
+       "e6cdkpy                                         0.4   \n",
+       "e5wc4tj                                         0.9   \n",
+       "e6ua0sb                                         0.5   \n",
+       "e5ua84v                                         0.6   \n",
        "\n",
-       "         2nd-largest / max[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                         0.333333   \n",
-       "e5ywqyk                                         0.500000   \n",
-       "e5qv9rj                                         1.000000   \n",
-       "e6jhojf                                         0.500000   \n",
-       "e6989ii                                         1.000000   \n",
-       "e69lgse                                         1.000000   \n",
-       "e5kwkg2                                         0.666667   \n",
-       "e6mehe7                                         0.666667   \n",
-       "e6m0hsd                                         0.500000   \n",
-       "e64r385                                         1.000000   \n",
-       "e5surbt                                         0.200000   \n",
-       "e58gxii                                         1.000000   \n",
-       "e64vc8y                                         0.166667   \n",
-       "e57504g                                         1.000000   \n",
-       "e5borjq                                         0.666667   \n",
-       "e64n9zv                                         0.500000   \n",
-       "e582ud3                                         0.333333   \n",
-       "e64i9cf                                         0.500000   \n",
-       "e6q9204                                         1.000000   \n",
-       "e5modd7                                         0.500000   \n",
-       "e5xhbyd                                         1.000000   \n",
-       "e5oaf7h                                         1.000000   \n",
-       "e6nir3u                                         1.000000   \n",
-       "e6c3xdn                                         0.500000   \n",
-       "e5d3zaa                                         1.000000   \n",
-       "e5gnjv9                                         0.125000   \n",
-       "e69gw2t                                         1.000000   \n",
-       "e5syrih                                         0.666667   \n",
-       "e5sa2yf                                         1.000000   \n",
-       "e6ai7z5                                         0.333333   \n",
-       "...                                                  ...   \n",
-       "e5smhzk                                         0.500000   \n",
-       "e5v91s0                                         0.400000   \n",
-       "e6n6di6                                         0.666667   \n",
-       "e6iqq30                                         0.166667   \n",
-       "e5bfad7                                         0.666667   \n",
-       "e6x5he5                                         0.250000   \n",
-       "e6l9uyf                                         0.400000   \n",
-       "e57hyr1                                         0.500000   \n",
-       "e5b8sj7                                         1.000000   \n",
-       "e6nlep7                                         0.000000   \n",
-       "e6ltazd                                         0.250000   \n",
-       "e57a6qq                                         1.000000   \n",
-       "e5qc7eb                                         0.666667   \n",
-       "e6hqt5y                                         1.000000   \n",
-       "e5ua84v                                         0.666667   \n",
-       "e65m7kq                                         0.500000   \n",
-       "e5ggtru                                         0.500000   \n",
-       "e5pmmig                                         0.500000   \n",
-       "e64l6vq                                         0.666667   \n",
-       "e6fjx0d                                         0.500000   \n",
-       "e5h3xyy                                         0.500000   \n",
-       "e589ri5                                         0.166667   \n",
-       "e5beuqa                                         0.666667   \n",
-       "e5lqoj1                                         0.200000   \n",
-       "e5kvch1                                         0.333333   \n",
-       "e6srvwm                                         0.666667   \n",
-       "e5o65mk                                         1.000000   \n",
-       "e647cm8                                         0.750000   \n",
-       "e58n526                                         0.000000   \n",
-       "e69r2kg                                         1.000000   \n",
+       "         prop-multiple[indegree over c->c responses]  \\\n",
+       "e5hm9mp                                     0.142857   \n",
+       "e5ytz1d                                     0.750000   \n",
+       "e6ls80j                                     0.500000   \n",
+       "e5mhgl5                                     0.285714   \n",
+       "e6w6fah                                     1.000000   \n",
+       "...                                              ...   \n",
+       "e65ca8k                                     0.125000   \n",
+       "e6cdkpy                                     0.750000   \n",
+       "e5wc4tj                                     0.000000   \n",
+       "e6ua0sb                                     0.400000   \n",
+       "e5ua84v                                     0.333333   \n",
        "\n",
-       "         2nd-largest / max[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.000000            \n",
-       "e5ywqyk                                           0.500000            \n",
-       "e5qv9rj                                           0.333333            \n",
-       "e6jhojf                                           0.500000            \n",
-       "e6989ii                                           0.500000            \n",
-       "e69lgse                                           0.333333            \n",
-       "e5kwkg2                                           0.500000            \n",
-       "e6mehe7                                           0.500000            \n",
-       "e6m0hsd                                           0.500000            \n",
-       "e64r385                                           1.000000            \n",
-       "e5surbt                                           1.000000            \n",
-       "e58gxii                                           1.000000            \n",
-       "e64vc8y                                           1.000000            \n",
-       "e57504g                                           1.000000            \n",
-       "e5borjq                                           0.666667            \n",
-       "e64n9zv                                           0.500000            \n",
-       "e582ud3                                           0.500000            \n",
-       "e64i9cf                                           0.500000            \n",
-       "e6q9204                                           1.000000            \n",
-       "e5modd7                                           0.500000            \n",
-       "e5xhbyd                                           1.000000            \n",
-       "e5oaf7h                                           1.000000            \n",
-       "e6nir3u                                           0.500000            \n",
-       "e6c3xdn                                           0.500000            \n",
-       "e5d3zaa                                           1.000000            \n",
-       "e5gnjv9                                           0.000000            \n",
-       "e69gw2t                                           1.000000            \n",
-       "e5syrih                                           0.666667            \n",
-       "e5sa2yf                                           1.000000            \n",
-       "e6ai7z5                                           1.000000            \n",
-       "...                                                    ...            \n",
-       "e5smhzk                                           1.000000            \n",
-       "e5v91s0                                           0.500000            \n",
-       "e6n6di6                                           0.666667            \n",
-       "e6iqq30                                           1.000000            \n",
-       "e5bfad7                                           1.000000            \n",
-       "e6x5he5                                           0.500000            \n",
-       "e6l9uyf                                           0.500000            \n",
-       "e57hyr1                                           0.500000            \n",
-       "e5b8sj7                                           0.666667            \n",
-       "e6nlep7                                                NaN            \n",
-       "e6ltazd                                           0.250000            \n",
-       "e57a6qq                                           1.000000            \n",
-       "e5qc7eb                                           0.666667            \n",
-       "e6hqt5y                                           0.250000            \n",
-       "e5ua84v                                           0.666667            \n",
-       "e65m7kq                                           0.500000            \n",
-       "e5ggtru                                           0.500000            \n",
-       "e5pmmig                                           0.500000            \n",
-       "e64l6vq                                           0.500000            \n",
-       "e6fjx0d                                           1.000000            \n",
-       "e5h3xyy                                           0.500000            \n",
-       "e589ri5                                           1.000000            \n",
-       "e5beuqa                                           0.333333            \n",
-       "e5lqoj1                                           1.000000            \n",
-       "e5kvch1                                           1.000000            \n",
-       "e6srvwm                                           1.000000            \n",
-       "e5o65mk                                           1.000000            \n",
-       "e647cm8                                           0.333333            \n",
-       "e58n526                                                NaN            \n",
-       "e69r2kg                                           1.000000            \n",
+       "         entropy[indegree over c->c responses]  \\\n",
+       "e5hm9mp                               1.831020   \n",
+       "e5ytz1d                               1.310784   \n",
+       "e6ls80j                               1.214890   \n",
+       "e5mhgl5                               1.889159   \n",
+       "e6w6fah                               0.000000   \n",
+       "...                                        ...   \n",
+       "e65ca8k                               2.043192   \n",
+       "e6cdkpy                               1.273028   \n",
+       "e5wc4tj                               2.197225   \n",
+       "e6ua0sb                               1.427061   \n",
+       "e5ua84v                               1.676988   \n",
        "\n",
        "         2nd-largest / max[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                         0.333333   \n",
-       "e5ywqyk                                         0.500000   \n",
-       "e5qv9rj                                         1.000000   \n",
-       "e6jhojf                                         0.500000   \n",
-       "e6989ii                                         0.500000   \n",
-       "e69lgse                                         1.000000   \n",
-       "e5kwkg2                                         0.666667   \n",
-       "e6mehe7                                         0.666667   \n",
-       "e6m0hsd                                         0.500000   \n",
-       "e64r385                                         1.000000   \n",
-       "e5surbt                                         0.200000   \n",
-       "e58gxii                                         1.000000   \n",
-       "e64vc8y                                         0.166667   \n",
-       "e57504g                                         1.000000   \n",
-       "e5borjq                                         0.666667   \n",
-       "e64n9zv                                         0.500000   \n",
-       "e582ud3                                         0.333333   \n",
-       "e64i9cf                                         0.500000   \n",
-       "e6q9204                                         1.000000   \n",
-       "e5modd7                                         0.500000   \n",
-       "e5xhbyd                                         1.000000   \n",
-       "e5oaf7h                                         1.000000   \n",
-       "e6nir3u                                         0.500000   \n",
-       "e6c3xdn                                         0.500000   \n",
-       "e5d3zaa                                         1.000000   \n",
-       "e5gnjv9                                         0.125000   \n",
-       "e69gw2t                                         1.000000   \n",
-       "e5syrih                                         0.666667   \n",
-       "e5sa2yf                                         1.000000   \n",
-       "e6ai7z5                                         0.333333   \n",
+       "e5hm9mp                                         0.333333   \n",
+       "e5ytz1d                                         1.000000   \n",
+       "e6ls80j                                         0.750000   \n",
+       "e5mhgl5                                         1.000000   \n",
+       "e6w6fah                                         0.000000   \n",
        "...                                                  ...   \n",
-       "e5smhzk                                         0.500000   \n",
-       "e5v91s0                                         0.400000   \n",
-       "e6n6di6                                         0.666667   \n",
-       "e6iqq30                                         0.166667   \n",
-       "e5bfad7                                         0.666667   \n",
-       "e6x5he5                                         0.500000   \n",
-       "e6l9uyf                                         0.400000   \n",
-       "e57hyr1                                         0.500000   \n",
-       "e5b8sj7                                         1.000000   \n",
-       "e6nlep7                                         0.000000   \n",
-       "e6ltazd                                         0.250000   \n",
-       "e57a6qq                                         1.000000   \n",
-       "e5qc7eb                                         0.666667   \n",
-       "e6hqt5y                                         1.000000   \n",
+       "e65ca8k                                         0.500000   \n",
+       "e6cdkpy                                         0.500000   \n",
+       "e5wc4tj                                         1.000000   \n",
+       "e6ua0sb                                         0.500000   \n",
        "e5ua84v                                         0.666667   \n",
-       "e65m7kq                                         0.500000   \n",
-       "e5ggtru                                         0.500000   \n",
-       "e5pmmig                                         0.500000   \n",
-       "e64l6vq                                         0.666667   \n",
-       "e6fjx0d                                         0.500000   \n",
-       "e5h3xyy                                         0.500000   \n",
-       "e589ri5                                         0.166667   \n",
-       "e5beuqa                                         0.666667   \n",
-       "e5lqoj1                                         0.200000   \n",
-       "e5kvch1                                         0.333333   \n",
-       "e6srvwm                                         0.666667   \n",
-       "e5o65mk                                         0.500000   \n",
-       "e647cm8                                         0.750000   \n",
-       "e58n526                                         0.000000   \n",
-       "e69r2kg                                         1.000000   \n",
        "\n",
-       "         2nd-largest / max[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.333333             \n",
-       "e5ywqyk                                           0.500000             \n",
-       "e5qv9rj                                           1.000000             \n",
-       "e6jhojf                                           0.250000             \n",
-       "e6989ii                                           1.000000             \n",
-       "e69lgse                                           0.500000             \n",
-       "e5kwkg2                                           1.000000             \n",
-       "e6mehe7                                           0.333333             \n",
-       "e6m0hsd                                           0.500000             \n",
-       "e64r385                                           0.500000             \n",
-       "e5surbt                                           1.000000             \n",
-       "e58gxii                                           0.333333             \n",
-       "e64vc8y                                           1.000000             \n",
-       "e57504g                                           0.500000             \n",
-       "e5borjq                                           1.000000             \n",
-       "e64n9zv                                           0.500000             \n",
-       "e582ud3                                           1.000000             \n",
-       "e64i9cf                                           0.500000             \n",
-       "e6q9204                                           0.500000             \n",
-       "e5modd7                                           1.000000             \n",
-       "e5xhbyd                                           1.000000             \n",
-       "e5oaf7h                                           0.500000             \n",
-       "e6nir3u                                           1.000000             \n",
-       "e6c3xdn                                           1.000000             \n",
-       "e5d3zaa                                           1.000000             \n",
-       "e5gnjv9                                           0.000000             \n",
-       "e69gw2t                                           0.500000             \n",
-       "e5syrih                                           0.500000             \n",
-       "e5sa2yf                                           1.000000             \n",
-       "e6ai7z5                                           0.250000             \n",
-       "...                                                    ...             \n",
-       "e5smhzk                                           0.500000             \n",
-       "e5v91s0                                           1.000000             \n",
-       "e6n6di6                                           0.500000             \n",
-       "e6iqq30                                           1.000000             \n",
-       "e5bfad7                                           0.500000             \n",
-       "e6x5he5                                           0.000000             \n",
-       "e6l9uyf                                           1.000000             \n",
-       "e57hyr1                                           1.000000             \n",
-       "e5b8sj7                                           1.000000             \n",
-       "e6nlep7                                                NaN             \n",
-       "e6ltazd                                           1.000000             \n",
-       "e57a6qq                                           0.500000             \n",
-       "e5qc7eb                                           1.000000             \n",
-       "e6hqt5y                                           1.000000             \n",
-       "e5ua84v                                           1.000000             \n",
-       "e65m7kq                                           1.000000             \n",
-       "e5ggtru                                           1.000000             \n",
-       "e5pmmig                                           1.000000             \n",
-       "e64l6vq                                           0.500000             \n",
-       "e6fjx0d                                           1.000000             \n",
-       "e5h3xyy                                           1.000000             \n",
-       "e589ri5                                           1.000000             \n",
-       "e5beuqa                                           0.333333             \n",
-       "e5lqoj1                                           0.500000             \n",
-       "e5kvch1                                           1.000000             \n",
-       "e6srvwm                                           1.000000             \n",
-       "e5o65mk                                           1.000000             \n",
-       "e647cm8                                           1.000000             \n",
-       "e58n526                                                NaN             \n",
-       "e69r2kg                                           0.500000             \n",
+       "         max[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                 2.0   \n",
+       "e5ytz1d                                 1.0   \n",
+       "e6ls80j                                 3.0   \n",
+       "e5mhgl5                                 2.0   \n",
+       "e6w6fah                                 1.0   \n",
+       "...                                     ...   \n",
+       "e65ca8k                                 8.0   \n",
+       "e6cdkpy                                 1.0   \n",
+       "e5wc4tj                                 5.0   \n",
+       "e6ua0sb                                 3.0   \n",
+       "e5ua84v                                 3.0   \n",
        "\n",
-       "         2nd-largest / max[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                          0.333333   \n",
-       "e5ywqyk                                          0.500000   \n",
-       "e5qv9rj                                          1.000000   \n",
-       "e6jhojf                                          0.250000   \n",
-       "e6989ii                                          1.000000   \n",
-       "e69lgse                                          0.500000   \n",
-       "e5kwkg2                                          1.000000   \n",
-       "e6mehe7                                          0.333333   \n",
-       "e6m0hsd                                          0.500000   \n",
-       "e64r385                                          1.000000   \n",
-       "e5surbt                                          1.000000   \n",
-       "e58gxii                                          0.333333   \n",
-       "e64vc8y                                          1.000000   \n",
-       "e57504g                                          1.000000   \n",
-       "e5borjq                                          0.500000   \n",
-       "e64n9zv                                          0.500000   \n",
-       "e582ud3                                          1.000000   \n",
-       "e64i9cf                                          0.500000   \n",
-       "e6q9204                                          0.333333   \n",
-       "e5modd7                                          1.000000   \n",
-       "e5xhbyd                                          1.000000   \n",
-       "e5oaf7h                                          0.500000   \n",
-       "e6nir3u                                          1.000000   \n",
-       "e6c3xdn                                          1.000000   \n",
-       "e5d3zaa                                          0.500000   \n",
-       "e5gnjv9                                          0.500000   \n",
-       "e69gw2t                                          1.000000   \n",
-       "e5syrih                                          1.000000   \n",
-       "e5sa2yf                                          1.000000   \n",
-       "e6ai7z5                                          0.250000   \n",
-       "...                                                   ...   \n",
-       "e5smhzk                                          0.500000   \n",
-       "e5v91s0                                          1.000000   \n",
-       "e6n6di6                                          0.500000   \n",
-       "e6iqq30                                          1.000000   \n",
-       "e5bfad7                                          0.500000   \n",
-       "e6x5he5                                          0.250000   \n",
-       "e6l9uyf                                          0.500000   \n",
-       "e57hyr1                                          1.000000   \n",
-       "e5b8sj7                                          0.500000   \n",
-       "e6nlep7                                          1.000000   \n",
-       "e6ltazd                                          0.500000   \n",
-       "e57a6qq                                          0.500000   \n",
-       "e5qc7eb                                          0.500000   \n",
-       "e6hqt5y                                          0.500000   \n",
-       "e5ua84v                                          0.666667   \n",
-       "e65m7kq                                          0.500000   \n",
-       "e5ggtru                                          0.500000   \n",
-       "e5pmmig                                          0.666667   \n",
-       "e64l6vq                                          0.500000   \n",
-       "e6fjx0d                                          0.500000   \n",
-       "e5h3xyy                                          0.500000   \n",
-       "e589ri5                                          1.000000   \n",
-       "e5beuqa                                          0.500000   \n",
-       "e5lqoj1                                          0.333333   \n",
-       "e5kvch1                                          1.000000   \n",
-       "e6srvwm                                          0.500000   \n",
-       "e5o65mk                                          1.000000   \n",
-       "e647cm8                                          1.000000   \n",
-       "e58n526                                          1.000000   \n",
-       "e69r2kg                                          0.500000   \n",
+       "         max[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                3.0   \n",
+       "e5ytz1d                                3.0   \n",
+       "e6ls80j                                4.0   \n",
+       "e5mhgl5                                2.0   \n",
+       "e6w6fah                                8.0   \n",
+       "...                                    ...   \n",
+       "e65ca8k                                2.0   \n",
+       "e6cdkpy                                4.0   \n",
+       "e5wc4tj                                1.0   \n",
+       "e6ua0sb                                4.0   \n",
+       "e5ua84v                                3.0   \n",
        "\n",
-       "         2nd-largest / max[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.333333             \n",
-       "e5ywqyk                                           0.750000             \n",
-       "e5qv9rj                                           1.000000             \n",
-       "e6jhojf                                           0.500000             \n",
-       "e6989ii                                           0.750000             \n",
-       "e69lgse                                           0.500000             \n",
-       "e5kwkg2                                           1.000000             \n",
-       "e6mehe7                                           0.666667             \n",
-       "e6m0hsd                                           0.750000             \n",
-       "e64r385                                           0.500000             \n",
-       "e5surbt                                           1.000000             \n",
-       "e58gxii                                           0.333333             \n",
-       "e64vc8y                                           1.000000             \n",
-       "e57504g                                           0.500000             \n",
-       "e5borjq                                           1.000000             \n",
-       "e64n9zv                                           1.000000             \n",
-       "e582ud3                                           1.000000             \n",
-       "e64i9cf                                           0.333333             \n",
-       "e6q9204                                           0.666667             \n",
-       "e5modd7                                           1.000000             \n",
-       "e5xhbyd                                           0.666667             \n",
-       "e5oaf7h                                           0.750000             \n",
-       "e6nir3u                                           0.750000             \n",
-       "e6c3xdn                                           1.000000             \n",
-       "e5d3zaa                                           1.000000             \n",
-       "e5gnjv9                                           0.000000             \n",
-       "e69gw2t                                           0.666667             \n",
-       "e5syrih                                           0.500000             \n",
-       "e5sa2yf                                           1.000000             \n",
-       "e6ai7z5                                           0.250000             \n",
-       "...                                                    ...             \n",
-       "e5smhzk                                           0.750000             \n",
-       "e5v91s0                                           1.000000             \n",
-       "e6n6di6                                           0.500000             \n",
-       "e6iqq30                                           1.000000             \n",
-       "e5bfad7                                           0.500000             \n",
-       "e6x5he5                                           0.000000             \n",
-       "e6l9uyf                                           1.000000             \n",
-       "e57hyr1                                           1.000000             \n",
-       "e5b8sj7                                           1.000000             \n",
-       "e6nlep7                                                NaN             \n",
-       "e6ltazd                                           0.666667             \n",
-       "e57a6qq                                           0.666667             \n",
-       "e5qc7eb                                           0.500000             \n",
-       "e6hqt5y                                           1.000000             \n",
-       "e5ua84v                                           1.000000             \n",
-       "e65m7kq                                           1.000000             \n",
-       "e5ggtru                                           1.000000             \n",
-       "e5pmmig                                           0.666667             \n",
-       "e64l6vq                                           0.333333             \n",
-       "e6fjx0d                                           0.750000             \n",
-       "e5h3xyy                                           1.000000             \n",
-       "e589ri5                                           1.000000             \n",
-       "e5beuqa                                           0.333333             \n",
-       "e5lqoj1                                           1.000000             \n",
-       "e5kvch1                                           0.500000             \n",
-       "e6srvwm                                           1.000000             \n",
-       "e5o65mk                                           0.750000             \n",
-       "e647cm8                                           1.000000             \n",
-       "e58n526                                                NaN             \n",
-       "e69r2kg                                           0.500000             \n",
+       "         argmax[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                    0.0   \n",
+       "e5ytz1d                                    0.0   \n",
+       "e6ls80j                                    3.0   \n",
+       "e5mhgl5                                    4.0   \n",
+       "e6w6fah                                    1.0   \n",
+       "...                                        ...   \n",
+       "e65ca8k                                    0.0   \n",
+       "e6cdkpy                                    1.0   \n",
+       "e5wc4tj                                    1.0   \n",
+       "e6ua0sb                                    2.0   \n",
+       "e5ua84v                                    1.0   \n",
        "\n",
-       "         2nd-largest / max[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                          0.666667   \n",
-       "e5ywqyk                                          0.750000   \n",
-       "e5qv9rj                                          1.000000   \n",
-       "e6jhojf                                          0.500000   \n",
-       "e6989ii                                          1.000000   \n",
-       "e69lgse                                          1.000000   \n",
-       "e5kwkg2                                          1.000000   \n",
-       "e6mehe7                                          0.666667   \n",
-       "e6m0hsd                                          0.600000   \n",
-       "e64r385                                          1.000000   \n",
-       "e5surbt                                          1.000000   \n",
-       "e58gxii                                          0.666667   \n",
-       "e64vc8y                                          1.000000   \n",
-       "e57504g                                          1.000000   \n",
-       "e5borjq                                          0.500000   \n",
-       "e64n9zv                                          0.750000   \n",
-       "e582ud3                                          1.000000   \n",
-       "e64i9cf                                          0.666667   \n",
-       "e6q9204                                          0.500000   \n",
-       "e5modd7                                          1.000000   \n",
-       "e5xhbyd                                          1.000000   \n",
-       "e5oaf7h                                          0.600000   \n",
-       "e6nir3u                                          1.000000   \n",
-       "e6c3xdn                                          1.000000   \n",
-       "e5d3zaa                                          0.666667   \n",
-       "e5gnjv9                                          0.500000   \n",
-       "e69gw2t                                          1.000000   \n",
-       "e5syrih                                          1.000000   \n",
-       "e5sa2yf                                          0.800000   \n",
-       "e6ai7z5                                          0.200000   \n",
-       "...                                                   ...   \n",
-       "e5smhzk                                          1.000000   \n",
-       "e5v91s0                                          1.000000   \n",
-       "e6n6di6                                          0.500000   \n",
-       "e6iqq30                                          1.000000   \n",
-       "e5bfad7                                          0.500000   \n",
-       "e6x5he5                                          0.250000   \n",
-       "e6l9uyf                                          0.500000   \n",
-       "e57hyr1                                          1.000000   \n",
-       "e5b8sj7                                          0.500000   \n",
-       "e6nlep7                                          1.000000   \n",
-       "e6ltazd                                          1.000000   \n",
-       "e57a6qq                                          1.000000   \n",
-       "e5qc7eb                                          1.000000   \n",
-       "e6hqt5y                                          0.500000   \n",
-       "e5ua84v                                          0.666667   \n",
-       "e65m7kq                                          0.500000   \n",
-       "e5ggtru                                          0.500000   \n",
-       "e5pmmig                                          1.000000   \n",
-       "e64l6vq                                          0.666667   \n",
-       "e6fjx0d                                          1.000000   \n",
-       "e5h3xyy                                          0.500000   \n",
-       "e589ri5                                          1.000000   \n",
-       "e5beuqa                                          0.500000   \n",
-       "e5lqoj1                                          0.666667   \n",
-       "e5kvch1                                          1.000000   \n",
-       "e6srvwm                                          0.500000   \n",
-       "e5o65mk                                          1.000000   \n",
-       "e647cm8                                          1.000000   \n",
-       "e58n526                                          1.000000   \n",
-       "e69r2kg                                          0.500000   \n",
+       "         argmax[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                   1.0   \n",
+       "e5ytz1d                                   0.0   \n",
+       "e6ls80j                                   0.0   \n",
+       "e5mhgl5                                   1.0   \n",
+       "e6w6fah                                   0.0   \n",
+       "...                                       ...   \n",
+       "e65ca8k                                   0.0   \n",
+       "e6cdkpy                                   0.0   \n",
+       "e5wc4tj                                   0.0   \n",
+       "e6ua0sb                                   2.0   \n",
+       "e5ua84v                                   1.0   \n",
        "\n",
-       "         2nd-largest[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0      \n",
-       "e5ywqyk                                                1.0      \n",
-       "e5qv9rj                                                1.0      \n",
-       "e6jhojf                                                1.0      \n",
-       "e6989ii                                                1.0      \n",
-       "e69lgse                                                1.0      \n",
-       "e5kwkg2                                                1.0      \n",
-       "e6mehe7                                                1.0      \n",
-       "e6m0hsd                                                1.0      \n",
-       "e64r385                                                2.0      \n",
-       "e5surbt                                                1.0      \n",
-       "e58gxii                                                2.0      \n",
-       "e64vc8y                                                1.0      \n",
-       "e57504g                                                2.0      \n",
-       "e5borjq                                                2.0      \n",
-       "e64n9zv                                                1.0      \n",
-       "e582ud3                                                1.0      \n",
-       "e64i9cf                                                1.0      \n",
-       "e6q9204                                                2.0      \n",
-       "e5modd7                                                2.0      \n",
-       "e5xhbyd                                                2.0      \n",
-       "e5oaf7h                                                1.0      \n",
-       "e6nir3u                                                1.0      \n",
-       "e6c3xdn                                                1.0      \n",
-       "e5d3zaa                                                2.0      \n",
-       "e5gnjv9                                                0.0      \n",
-       "e69gw2t                                                2.0      \n",
-       "e5syrih                                                2.0      \n",
-       "e5sa2yf                                                1.0      \n",
-       "e6ai7z5                                                1.0      \n",
-       "...                                                    ...      \n",
-       "e5smhzk                                                1.0      \n",
-       "e5v91s0                                                1.0      \n",
-       "e6n6di6                                                2.0      \n",
-       "e6iqq30                                                1.0      \n",
-       "e5bfad7                                                2.0      \n",
-       "e6x5he5                                                1.0      \n",
-       "e6l9uyf                                                1.0      \n",
-       "e57hyr1                                                1.0      \n",
-       "e5b8sj7                                                2.0      \n",
-       "e6nlep7                                                0.0      \n",
-       "e6ltazd                                                1.0      \n",
-       "e57a6qq                                                2.0      \n",
-       "e5qc7eb                                                2.0      \n",
-       "e6hqt5y                                                1.0      \n",
-       "e5ua84v                                                2.0      \n",
-       "e65m7kq                                                1.0      \n",
-       "e5ggtru                                                2.0      \n",
-       "e5pmmig                                                2.0      \n",
-       "e64l6vq                                                1.0      \n",
-       "e6fjx0d                                                1.0      \n",
-       "e5h3xyy                                                1.0      \n",
-       "e589ri5                                                1.0      \n",
-       "e5beuqa                                                1.0      \n",
-       "e5lqoj1                                                1.0      \n",
-       "e5kvch1                                                1.0      \n",
-       "e6srvwm                                                2.0      \n",
-       "e5o65mk                                                1.0      \n",
-       "e647cm8                                                1.0      \n",
-       "e58n526                                                0.0      \n",
-       "e69r2kg                                                2.0      \n",
+       "         norm.max[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                 0.222222   \n",
+       "e5ytz1d                                 0.111111   \n",
+       "e6ls80j                                 0.333333   \n",
+       "e5mhgl5                                 0.222222   \n",
+       "e6w6fah                                 0.125000   \n",
+       "...                                          ...   \n",
+       "e65ca8k                                 0.888889   \n",
+       "e6cdkpy                                 0.111111   \n",
+       "e5wc4tj                                 0.555556   \n",
+       "e6ua0sb                                 0.333333   \n",
+       "e5ua84v                                 0.333333   \n",
        "\n",
-       "         2nd-largest[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                        1.0   \n",
-       "e5ywqyk                                        2.0   \n",
-       "e5qv9rj                                        3.0   \n",
-       "e6jhojf                                        1.0   \n",
-       "e6989ii                                        1.0   \n",
-       "e69lgse                                        3.0   \n",
-       "e5kwkg2                                        2.0   \n",
-       "e6mehe7                                        2.0   \n",
-       "e6m0hsd                                        1.0   \n",
-       "e64r385                                        2.0   \n",
-       "e5surbt                                        1.0   \n",
-       "e58gxii                                        2.0   \n",
-       "e64vc8y                                        1.0   \n",
-       "e57504g                                        2.0   \n",
-       "e5borjq                                        2.0   \n",
-       "e64n9zv                                        1.0   \n",
-       "e582ud3                                        2.0   \n",
-       "e64i9cf                                        2.0   \n",
-       "e6q9204                                        2.0   \n",
-       "e5modd7                                        2.0   \n",
-       "e5xhbyd                                        2.0   \n",
-       "e5oaf7h                                        1.0   \n",
-       "e6nir3u                                        1.0   \n",
-       "e6c3xdn                                        1.0   \n",
-       "e5d3zaa                                        2.0   \n",
-       "e5gnjv9                                        1.0   \n",
-       "e69gw2t                                        2.0   \n",
-       "e5syrih                                        2.0   \n",
-       "e5sa2yf                                        1.0   \n",
-       "e6ai7z5                                        2.0   \n",
-       "...                                            ...   \n",
-       "e5smhzk                                        1.0   \n",
-       "e5v91s0                                        2.0   \n",
-       "e6n6di6                                        2.0   \n",
-       "e6iqq30                                        1.0   \n",
-       "e5bfad7                                        2.0   \n",
-       "e6x5he5                                        1.0   \n",
-       "e6l9uyf                                        2.0   \n",
-       "e57hyr1                                        2.0   \n",
-       "e5b8sj7                                        3.0   \n",
-       "e6nlep7                                        0.0   \n",
-       "e6ltazd                                        1.0   \n",
-       "e57a6qq                                        2.0   \n",
-       "e5qc7eb                                        3.0   \n",
-       "e6hqt5y                                        4.0   \n",
-       "e5ua84v                                        2.0   \n",
-       "e65m7kq                                        3.0   \n",
-       "e5ggtru                                        2.0   \n",
-       "e5pmmig                                        2.0   \n",
-       "e64l6vq                                        2.0   \n",
-       "e6fjx0d                                        1.0   \n",
-       "e5h3xyy                                        2.0   \n",
-       "e589ri5                                        1.0   \n",
-       "e5beuqa                                        2.0   \n",
-       "e5lqoj1                                        1.0   \n",
-       "e5kvch1                                        2.0   \n",
-       "e6srvwm                                        2.0   \n",
-       "e5o65mk                                        1.0   \n",
-       "e647cm8                                        3.0   \n",
-       "e58n526                                        0.0   \n",
-       "e69r2kg                                        2.0   \n",
+       "         norm.max[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                0.333333   \n",
+       "e5ytz1d                                0.333333   \n",
+       "e6ls80j                                0.444444   \n",
+       "e5mhgl5                                0.222222   \n",
+       "e6w6fah                                1.000000   \n",
+       "...                                         ...   \n",
+       "e65ca8k                                0.222222   \n",
+       "e6cdkpy                                0.444444   \n",
+       "e5wc4tj                                0.111111   \n",
+       "e6ua0sb                                0.444444   \n",
+       "e5ua84v                                0.333333   \n",
        "\n",
-       "         2nd-largest[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0      \n",
-       "e5ywqyk                                                1.0      \n",
-       "e5qv9rj                                                1.0      \n",
-       "e6jhojf                                                1.0      \n",
-       "e6989ii                                                1.0      \n",
-       "e69lgse                                                1.0      \n",
-       "e5kwkg2                                                1.0      \n",
-       "e6mehe7                                                1.0      \n",
-       "e6m0hsd                                                1.0      \n",
-       "e64r385                                                2.0      \n",
-       "e5surbt                                                1.0      \n",
-       "e58gxii                                                2.0      \n",
-       "e64vc8y                                                1.0      \n",
-       "e57504g                                                2.0      \n",
-       "e5borjq                                                2.0      \n",
-       "e64n9zv                                                1.0      \n",
-       "e582ud3                                                1.0      \n",
-       "e64i9cf                                                1.0      \n",
-       "e6q9204                                                2.0      \n",
-       "e5modd7                                                2.0      \n",
-       "e5xhbyd                                                2.0      \n",
-       "e5oaf7h                                                2.0      \n",
-       "e6nir3u                                                1.0      \n",
-       "e6c3xdn                                                1.0      \n",
-       "e5d3zaa                                                2.0      \n",
-       "e5gnjv9                                                0.0      \n",
-       "e69gw2t                                                2.0      \n",
-       "e5syrih                                                2.0      \n",
-       "e5sa2yf                                                1.0      \n",
-       "e6ai7z5                                                1.0      \n",
-       "...                                                    ...      \n",
-       "e5smhzk                                                1.0      \n",
-       "e5v91s0                                                1.0      \n",
-       "e6n6di6                                                2.0      \n",
-       "e6iqq30                                                1.0      \n",
-       "e5bfad7                                                2.0      \n",
-       "e6x5he5                                                1.0      \n",
-       "e6l9uyf                                                1.0      \n",
-       "e57hyr1                                                1.0      \n",
-       "e5b8sj7                                                2.0      \n",
-       "e6nlep7                                                0.0      \n",
-       "e6ltazd                                                1.0      \n",
-       "e57a6qq                                                2.0      \n",
-       "e5qc7eb                                                2.0      \n",
-       "e6hqt5y                                                1.0      \n",
-       "e5ua84v                                                2.0      \n",
-       "e65m7kq                                                1.0      \n",
-       "e5ggtru                                                2.0      \n",
-       "e5pmmig                                                1.0      \n",
-       "e64l6vq                                                1.0      \n",
-       "e6fjx0d                                                1.0      \n",
-       "e5h3xyy                                                1.0      \n",
-       "e589ri5                                                1.0      \n",
-       "e5beuqa                                                1.0      \n",
-       "e5lqoj1                                                1.0      \n",
-       "e5kvch1                                                1.0      \n",
-       "e6srvwm                                                2.0      \n",
-       "e5o65mk                                                1.0      \n",
-       "e647cm8                                                1.0      \n",
-       "e58n526                                                0.0      \n",
-       "e69r2kg                                                2.0      \n",
+       "         2nd-largest[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                         2.0   \n",
+       "e5ytz1d                                         1.0   \n",
+       "e6ls80j                                         2.0   \n",
+       "e5mhgl5                                         2.0   \n",
+       "e6w6fah                                         1.0   \n",
+       "...                                             ...   \n",
+       "e65ca8k                                         1.0   \n",
+       "e6cdkpy                                         1.0   \n",
+       "e5wc4tj                                         4.0   \n",
+       "e6ua0sb                                         2.0   \n",
+       "e5ua84v                                         2.0   \n",
        "\n",
        "         2nd-largest[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                        1.0   \n",
-       "e5ywqyk                                        1.0   \n",
-       "e5qv9rj                                        3.0   \n",
-       "e6jhojf                                        1.0   \n",
-       "e6989ii                                        1.0   \n",
-       "e69lgse                                        3.0   \n",
-       "e5kwkg2                                        2.0   \n",
-       "e6mehe7                                        2.0   \n",
-       "e6m0hsd                                        1.0   \n",
-       "e64r385                                        2.0   \n",
-       "e5surbt                                        1.0   \n",
-       "e58gxii                                        2.0   \n",
-       "e64vc8y                                        1.0   \n",
-       "e57504g                                        2.0   \n",
-       "e5borjq                                        2.0   \n",
-       "e64n9zv                                        1.0   \n",
-       "e582ud3                                        2.0   \n",
-       "e64i9cf                                        2.0   \n",
-       "e6q9204                                        2.0   \n",
-       "e5modd7                                        2.0   \n",
-       "e5xhbyd                                        2.0   \n",
-       "e5oaf7h                                        2.0   \n",
-       "e6nir3u                                        1.0   \n",
-       "e6c3xdn                                        1.0   \n",
-       "e5d3zaa                                        2.0   \n",
-       "e5gnjv9                                        1.0   \n",
-       "e69gw2t                                        2.0   \n",
-       "e5syrih                                        2.0   \n",
-       "e5sa2yf                                        1.0   \n",
-       "e6ai7z5                                        1.0   \n",
+       "e5hm9mp                                        1.0   \n",
+       "e5ytz1d                                        3.0   \n",
+       "e6ls80j                                        3.0   \n",
+       "e5mhgl5                                        2.0   \n",
+       "e6w6fah                                        0.0   \n",
        "...                                            ...   \n",
-       "e5smhzk                                        1.0   \n",
-       "e5v91s0                                        2.0   \n",
-       "e6n6di6                                        2.0   \n",
-       "e6iqq30                                        1.0   \n",
-       "e5bfad7                                        2.0   \n",
-       "e6x5he5                                        1.0   \n",
-       "e6l9uyf                                        2.0   \n",
-       "e57hyr1                                        2.0   \n",
-       "e5b8sj7                                        3.0   \n",
-       "e6nlep7                                        0.0   \n",
-       "e6ltazd                                        1.0   \n",
-       "e57a6qq                                        2.0   \n",
-       "e5qc7eb                                        2.0   \n",
-       "e6hqt5y                                        4.0   \n",
+       "e65ca8k                                        1.0   \n",
+       "e6cdkpy                                        2.0   \n",
+       "e5wc4tj                                        1.0   \n",
+       "e6ua0sb                                        2.0   \n",
        "e5ua84v                                        2.0   \n",
-       "e65m7kq                                        2.0   \n",
-       "e5ggtru                                        2.0   \n",
-       "e5pmmig                                        1.0   \n",
-       "e64l6vq                                        2.0   \n",
-       "e6fjx0d                                        1.0   \n",
-       "e5h3xyy                                        2.0   \n",
-       "e589ri5                                        1.0   \n",
-       "e5beuqa                                        2.0   \n",
-       "e5lqoj1                                        1.0   \n",
-       "e5kvch1                                        1.0   \n",
-       "e6srvwm                                        2.0   \n",
-       "e5o65mk                                        1.0   \n",
-       "e647cm8                                        3.0   \n",
-       "e58n526                                        0.0   \n",
-       "e69r2kg                                        2.0   \n",
-       "\n",
-       "         2nd-largest[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0      \n",
-       "e5ywqyk                                                1.0      \n",
-       "e5qv9rj                                                1.0      \n",
-       "e6jhojf                                                1.0      \n",
-       "e6989ii                                                1.0      \n",
-       "e69lgse                                                1.0      \n",
-       "e5kwkg2                                                1.0      \n",
-       "e6mehe7                                                1.0      \n",
-       "e6m0hsd                                                1.0      \n",
-       "e64r385                                                2.0      \n",
-       "e5surbt                                                1.0      \n",
-       "e58gxii                                                2.0      \n",
-       "e64vc8y                                                1.0      \n",
-       "e57504g                                                2.0      \n",
-       "e5borjq                                                2.0      \n",
-       "e64n9zv                                                1.0      \n",
-       "e582ud3                                                1.0      \n",
-       "e64i9cf                                                1.0      \n",
-       "e6q9204                                                2.0      \n",
-       "e5modd7                                                2.0      \n",
-       "e5xhbyd                                                2.0      \n",
-       "e5oaf7h                                                2.0      \n",
-       "e6nir3u                                                1.0      \n",
-       "e6c3xdn                                                1.0      \n",
-       "e5d3zaa                                                2.0      \n",
-       "e5gnjv9                                                0.0      \n",
-       "e69gw2t                                                2.0      \n",
-       "e5syrih                                                2.0      \n",
-       "e5sa2yf                                                1.0      \n",
-       "e6ai7z5                                                1.0      \n",
-       "...                                                    ...      \n",
-       "e5smhzk                                                1.0      \n",
-       "e5v91s0                                                1.0      \n",
-       "e6n6di6                                                2.0      \n",
-       "e6iqq30                                                1.0      \n",
-       "e5bfad7                                                2.0      \n",
-       "e6x5he5                                                1.0      \n",
-       "e6l9uyf                                                1.0      \n",
-       "e57hyr1                                                1.0      \n",
-       "e5b8sj7                                                2.0      \n",
-       "e6nlep7                                                0.0      \n",
-       "e6ltazd                                                1.0      \n",
-       "e57a6qq                                                2.0      \n",
-       "e5qc7eb                                                2.0      \n",
-       "e6hqt5y                                                1.0      \n",
-       "e5ua84v                                                2.0      \n",
-       "e65m7kq                                                1.0      \n",
-       "e5ggtru                                                2.0      \n",
-       "e5pmmig                                                1.0      \n",
-       "e64l6vq                                                1.0      \n",
-       "e6fjx0d                                                1.0      \n",
-       "e5h3xyy                                                1.0      \n",
-       "e589ri5                                                1.0      \n",
-       "e5beuqa                                                1.0      \n",
-       "e5lqoj1                                                1.0      \n",
-       "e5kvch1                                                1.0      \n",
-       "e6srvwm                                                2.0      \n",
-       "e5o65mk                                                1.0      \n",
-       "e647cm8                                                1.0      \n",
-       "e58n526                                                0.0      \n",
-       "e69r2kg                                                2.0      \n",
        "\n",
-       "         2nd-largest[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                        1.0   \n",
-       "e5ywqyk                                        1.0   \n",
-       "e5qv9rj                                        3.0   \n",
-       "e6jhojf                                        1.0   \n",
-       "e6989ii                                        1.0   \n",
-       "e69lgse                                        3.0   \n",
-       "e5kwkg2                                        2.0   \n",
-       "e6mehe7                                        2.0   \n",
-       "e6m0hsd                                        1.0   \n",
-       "e64r385                                        2.0   \n",
-       "e5surbt                                        1.0   \n",
-       "e58gxii                                        2.0   \n",
-       "e64vc8y                                        1.0   \n",
-       "e57504g                                        2.0   \n",
-       "e5borjq                                        2.0   \n",
-       "e64n9zv                                        1.0   \n",
-       "e582ud3                                        2.0   \n",
-       "e64i9cf                                        2.0   \n",
-       "e6q9204                                        2.0   \n",
-       "e5modd7                                        2.0   \n",
-       "e5xhbyd                                        2.0   \n",
-       "e5oaf7h                                        2.0   \n",
-       "e6nir3u                                        1.0   \n",
-       "e6c3xdn                                        1.0   \n",
-       "e5d3zaa                                        2.0   \n",
-       "e5gnjv9                                        1.0   \n",
-       "e69gw2t                                        2.0   \n",
-       "e5syrih                                        2.0   \n",
-       "e5sa2yf                                        1.0   \n",
-       "e6ai7z5                                        1.0   \n",
+       "         2nd-argmax[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                        2.0   \n",
+       "e5ytz1d                                        1.0   \n",
+       "e6ls80j                                        2.0   \n",
+       "e5mhgl5                                        6.0   \n",
+       "e6w6fah                                        2.0   \n",
        "...                                            ...   \n",
-       "e5smhzk                                        1.0   \n",
-       "e5v91s0                                        2.0   \n",
-       "e6n6di6                                        2.0   \n",
-       "e6iqq30                                        1.0   \n",
-       "e5bfad7                                        2.0   \n",
-       "e6x5he5                                        2.0   \n",
-       "e6l9uyf                                        2.0   \n",
-       "e57hyr1                                        2.0   \n",
-       "e5b8sj7                                        3.0   \n",
-       "e6nlep7                                        0.0   \n",
-       "e6ltazd                                        1.0   \n",
-       "e57a6qq                                        2.0   \n",
-       "e5qc7eb                                        2.0   \n",
-       "e6hqt5y                                        4.0   \n",
-       "e5ua84v                                        2.0   \n",
-       "e65m7kq                                        2.0   \n",
-       "e5ggtru                                        2.0   \n",
-       "e5pmmig                                        1.0   \n",
-       "e64l6vq                                        2.0   \n",
-       "e6fjx0d                                        1.0   \n",
-       "e5h3xyy                                        2.0   \n",
-       "e589ri5                                        1.0   \n",
-       "e5beuqa                                        2.0   \n",
-       "e5lqoj1                                        1.0   \n",
-       "e5kvch1                                        1.0   \n",
-       "e6srvwm                                        2.0   \n",
-       "e5o65mk                                        1.0   \n",
-       "e647cm8                                        3.0   \n",
-       "e58n526                                        0.0   \n",
-       "e69r2kg                                        2.0   \n",
+       "e65ca8k                                        1.0   \n",
+       "e6cdkpy                                        2.0   \n",
+       "e5wc4tj                                        0.0   \n",
+       "e6ua0sb                                        1.0   \n",
+       "e5ua84v                                        4.0   \n",
        "\n",
-       "         2nd-largest[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0       \n",
-       "e5ywqyk                                                1.0       \n",
-       "e5qv9rj                                                1.0       \n",
-       "e6jhojf                                                1.0       \n",
-       "e6989ii                                                1.0       \n",
-       "e69lgse                                                1.0       \n",
-       "e5kwkg2                                                1.0       \n",
-       "e6mehe7                                                1.0       \n",
-       "e6m0hsd                                                1.0       \n",
-       "e64r385                                                1.0       \n",
-       "e5surbt                                                1.0       \n",
-       "e58gxii                                                1.0       \n",
-       "e64vc8y                                                1.0       \n",
-       "e57504g                                                1.0       \n",
-       "e5borjq                                                1.0       \n",
-       "e64n9zv                                                1.0       \n",
-       "e582ud3                                                1.0       \n",
-       "e64i9cf                                                1.0       \n",
-       "e6q9204                                                1.0       \n",
-       "e5modd7                                                1.0       \n",
-       "e5xhbyd                                                2.0       \n",
-       "e5oaf7h                                                1.0       \n",
-       "e6nir3u                                                1.0       \n",
-       "e6c3xdn                                                1.0       \n",
-       "e5d3zaa                                                1.0       \n",
-       "e5gnjv9                                                0.0       \n",
-       "e69gw2t                                                1.0       \n",
-       "e5syrih                                                1.0       \n",
-       "e5sa2yf                                                1.0       \n",
-       "e6ai7z5                                                1.0       \n",
-       "...                                                    ...       \n",
-       "e5smhzk                                                1.0       \n",
-       "e5v91s0                                                1.0       \n",
-       "e6n6di6                                                1.0       \n",
-       "e6iqq30                                                1.0       \n",
-       "e5bfad7                                                1.0       \n",
-       "e6x5he5                                                0.0       \n",
-       "e6l9uyf                                                1.0       \n",
-       "e57hyr1                                                1.0       \n",
-       "e5b8sj7                                                1.0       \n",
-       "e6nlep7                                                0.0       \n",
-       "e6ltazd                                                1.0       \n",
-       "e57a6qq                                                1.0       \n",
-       "e5qc7eb                                                1.0       \n",
-       "e6hqt5y                                                1.0       \n",
-       "e5ua84v                                                2.0       \n",
-       "e65m7kq                                                1.0       \n",
-       "e5ggtru                                                1.0       \n",
-       "e5pmmig                                                2.0       \n",
-       "e64l6vq                                                1.0       \n",
-       "e6fjx0d                                                1.0       \n",
-       "e5h3xyy                                                1.0       \n",
-       "e589ri5                                                1.0       \n",
-       "e5beuqa                                                1.0       \n",
-       "e5lqoj1                                                1.0       \n",
-       "e5kvch1                                                1.0       \n",
-       "e6srvwm                                                1.0       \n",
-       "e5o65mk                                                1.0       \n",
-       "e647cm8                                                1.0       \n",
-       "e58n526                                                0.0       \n",
-       "e69r2kg                                                1.0       \n",
+       "         2nd-argmax[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                       0.0   \n",
+       "e5ytz1d                                       2.0   \n",
+       "e6ls80j                                       2.0   \n",
+       "e5mhgl5                                       4.0   \n",
+       "e6w6fah                                       1.0   \n",
+       "...                                           ...   \n",
+       "e65ca8k                                       2.0   \n",
+       "e6cdkpy                                       1.0   \n",
+       "e5wc4tj                                       1.0   \n",
+       "e6ua0sb                                       0.0   \n",
+       "e5ua84v                                       5.0   \n",
        "\n",
-       "         2nd-largest[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                         1.0   \n",
-       "e5ywqyk                                         1.0   \n",
-       "e5qv9rj                                         1.0   \n",
-       "e6jhojf                                         1.0   \n",
-       "e6989ii                                         1.0   \n",
-       "e69lgse                                         1.0   \n",
-       "e5kwkg2                                         1.0   \n",
-       "e6mehe7                                         1.0   \n",
-       "e6m0hsd                                         1.0   \n",
-       "e64r385                                         2.0   \n",
-       "e5surbt                                         1.0   \n",
-       "e58gxii                                         1.0   \n",
-       "e64vc8y                                         1.0   \n",
-       "e57504g                                         2.0   \n",
-       "e5borjq                                         1.0   \n",
-       "e64n9zv                                         1.0   \n",
-       "e582ud3                                         1.0   \n",
-       "e64i9cf                                         1.0   \n",
-       "e6q9204                                         1.0   \n",
-       "e5modd7                                         1.0   \n",
-       "e5xhbyd                                         2.0   \n",
-       "e5oaf7h                                         1.0   \n",
-       "e6nir3u                                         1.0   \n",
-       "e6c3xdn                                         1.0   \n",
-       "e5d3zaa                                         1.0   \n",
-       "e5gnjv9                                         1.0   \n",
-       "e69gw2t                                         2.0   \n",
-       "e5syrih                                         2.0   \n",
-       "e5sa2yf                                         1.0   \n",
-       "e6ai7z5                                         1.0   \n",
+       "         norm.2nd-largest[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                         0.222222   \n",
+       "e5ytz1d                                         0.111111   \n",
+       "e6ls80j                                         0.222222   \n",
+       "e5mhgl5                                         0.222222   \n",
+       "e6w6fah                                         0.125000   \n",
+       "...                                                  ...   \n",
+       "e65ca8k                                         0.111111   \n",
+       "e6cdkpy                                         0.111111   \n",
+       "e5wc4tj                                         0.444444   \n",
+       "e6ua0sb                                         0.222222   \n",
+       "e5ua84v                                         0.222222   \n",
+       "\n",
+       "         norm.2nd-largest[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                        0.111111   \n",
+       "e5ytz1d                                        0.333333   \n",
+       "e6ls80j                                        0.333333   \n",
+       "e5mhgl5                                        0.222222   \n",
+       "e6w6fah                                        0.000000   \n",
+       "...                                                 ...   \n",
+       "e65ca8k                                        0.111111   \n",
+       "e6cdkpy                                        0.222222   \n",
+       "e5wc4tj                                        0.111111   \n",
+       "e6ua0sb                                        0.222222   \n",
+       "e5ua84v                                        0.222222   \n",
+       "\n",
+       "         mean[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                             1.800000   \n",
+       "e5ytz1d                             1.000000   \n",
+       "e6ls80j                             1.285714   \n",
+       "e5mhgl5                             1.125000   \n",
+       "e6w6fah                             0.888889   \n",
+       "...                                      ...   \n",
+       "e65ca8k                             4.500000   \n",
+       "e6cdkpy                             0.900000   \n",
+       "e5wc4tj                             4.500000   \n",
+       "e6ua0sb                             1.800000   \n",
+       "e5ua84v                             1.285714   \n",
+       "\n",
+       "         mean[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                 0.9   \n",
+       "e5ytz1d                                 0.9   \n",
+       "e6ls80j                                 0.9   \n",
+       "e5mhgl5                                 0.9   \n",
+       "e6w6fah                                 0.8   \n",
+       "...                                     ...   \n",
+       "e65ca8k                                 0.9   \n",
+       "e6cdkpy                                 0.9   \n",
+       "e5wc4tj                                 0.9   \n",
+       "e6ua0sb                                 0.9   \n",
+       "e5ua84v                                 0.9   \n",
+       "\n",
+       "         mean-nonzero[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                     1.800000   \n",
+       "e5ytz1d                                     1.000000   \n",
+       "e6ls80j                                     1.500000   \n",
+       "e5mhgl5                                     1.285714   \n",
+       "e6w6fah                                     1.000000   \n",
+       "...                                              ...   \n",
+       "e65ca8k                                     4.500000   \n",
+       "e6cdkpy                                     1.000000   \n",
+       "e5wc4tj                                     4.500000   \n",
+       "e6ua0sb                                     1.800000   \n",
+       "e5ua84v                                     1.500000   \n",
+       "\n",
+       "         mean-nonzero[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                    1.285714   \n",
+       "e5ytz1d                                    2.250000   \n",
+       "e6ls80j                                    2.250000   \n",
+       "e5mhgl5                                    1.285714   \n",
+       "e6w6fah                                    8.000000   \n",
        "...                                             ...   \n",
-       "e5smhzk                                         1.0   \n",
-       "e5v91s0                                         1.0   \n",
-       "e6n6di6                                         1.0   \n",
-       "e6iqq30                                         1.0   \n",
-       "e5bfad7                                         1.0   \n",
-       "e6x5he5                                         1.0   \n",
-       "e6l9uyf                                         1.0   \n",
-       "e57hyr1                                         2.0   \n",
-       "e5b8sj7                                         1.0   \n",
-       "e6nlep7                                         1.0   \n",
-       "e6ltazd                                         1.0   \n",
-       "e57a6qq                                         1.0   \n",
-       "e5qc7eb                                         1.0   \n",
-       "e6hqt5y                                         1.0   \n",
-       "e5ua84v                                         2.0   \n",
-       "e65m7kq                                         1.0   \n",
-       "e5ggtru                                         1.0   \n",
-       "e5pmmig                                         2.0   \n",
-       "e64l6vq                                         1.0   \n",
-       "e6fjx0d                                         1.0   \n",
-       "e5h3xyy                                         1.0   \n",
-       "e589ri5                                         1.0   \n",
-       "e5beuqa                                         2.0   \n",
-       "e5lqoj1                                         1.0   \n",
-       "e5kvch1                                         2.0   \n",
-       "e6srvwm                                         1.0   \n",
-       "e5o65mk                                         1.0   \n",
-       "e647cm8                                         1.0   \n",
-       "e58n526                                         1.0   \n",
-       "e69r2kg                                         1.0   \n",
+       "e65ca8k                                    1.125000   \n",
+       "e6cdkpy                                    2.250000   \n",
+       "e5wc4tj                                    1.000000   \n",
+       "e6ua0sb                                    1.800000   \n",
+       "e5ua84v                                    1.500000   \n",
        "\n",
-       "         2nd-largest[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                                1.0       \n",
-       "e5ywqyk                                                3.0       \n",
-       "e5qv9rj                                                1.0       \n",
-       "e6jhojf                                                2.0       \n",
-       "e6989ii                                                3.0       \n",
-       "e69lgse                                                1.0       \n",
-       "e5kwkg2                                                1.0       \n",
-       "e6mehe7                                                2.0       \n",
-       "e6m0hsd                                                3.0       \n",
-       "e64r385                                                1.0       \n",
-       "e5surbt                                                1.0       \n",
-       "e58gxii                                                1.0       \n",
-       "e64vc8y                                                1.0       \n",
-       "e57504g                                                1.0       \n",
-       "e5borjq                                                1.0       \n",
-       "e64n9zv                                                3.0       \n",
-       "e582ud3                                                1.0       \n",
-       "e64i9cf                                                1.0       \n",
-       "e6q9204                                                2.0       \n",
-       "e5modd7                                                1.0       \n",
-       "e5xhbyd                                                2.0       \n",
-       "e5oaf7h                                                3.0       \n",
-       "e6nir3u                                                3.0       \n",
-       "e6c3xdn                                                1.0       \n",
-       "e5d3zaa                                                2.0       \n",
-       "e5gnjv9                                                0.0       \n",
-       "e69gw2t                                                2.0       \n",
-       "e5syrih                                                1.0       \n",
-       "e5sa2yf                                                4.0       \n",
-       "e6ai7z5                                                1.0       \n",
-       "...                                                    ...       \n",
-       "e5smhzk                                                3.0       \n",
-       "e5v91s0                                                1.0       \n",
-       "e6n6di6                                                1.0       \n",
-       "e6iqq30                                                1.0       \n",
-       "e5bfad7                                                1.0       \n",
-       "e6x5he5                                                0.0       \n",
-       "e6l9uyf                                                1.0       \n",
-       "e57hyr1                                                1.0       \n",
-       "e5b8sj7                                                1.0       \n",
-       "e6nlep7                                                0.0       \n",
-       "e6ltazd                                                2.0       \n",
-       "e57a6qq                                                2.0       \n",
-       "e5qc7eb                                                1.0       \n",
-       "e6hqt5y                                                1.0       \n",
-       "e5ua84v                                                2.0       \n",
-       "e65m7kq                                                1.0       \n",
-       "e5ggtru                                                1.0       \n",
-       "e5pmmig                                                2.0       \n",
-       "e64l6vq                                                1.0       \n",
-       "e6fjx0d                                                3.0       \n",
-       "e5h3xyy                                                1.0       \n",
-       "e589ri5                                                1.0       \n",
-       "e5beuqa                                                1.0       \n",
-       "e5lqoj1                                                2.0       \n",
-       "e5kvch1                                                1.0       \n",
-       "e6srvwm                                                1.0       \n",
-       "e5o65mk                                                3.0       \n",
-       "e647cm8                                                1.0       \n",
-       "e58n526                                                0.0       \n",
-       "e69r2kg                                                1.0       \n",
+       "         prop-nonzero[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                     1.000000   \n",
+       "e5ytz1d                                     1.000000   \n",
+       "e6ls80j                                     0.857143   \n",
+       "e5mhgl5                                     0.875000   \n",
+       "e6w6fah                                     0.888889   \n",
+       "...                                              ...   \n",
+       "e65ca8k                                     1.000000   \n",
+       "e6cdkpy                                     0.900000   \n",
+       "e5wc4tj                                     1.000000   \n",
+       "e6ua0sb                                     1.000000   \n",
+       "e5ua84v                                     0.857143   \n",
        "\n",
-       "         2nd-largest[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                         2.0   \n",
-       "e5ywqyk                                         3.0   \n",
-       "e5qv9rj                                         1.0   \n",
-       "e6jhojf                                         2.0   \n",
-       "e6989ii                                         4.0   \n",
-       "e69lgse                                         2.0   \n",
-       "e5kwkg2                                         1.0   \n",
-       "e6mehe7                                         2.0   \n",
-       "e6m0hsd                                         3.0   \n",
-       "e64r385                                         2.0   \n",
-       "e5surbt                                         1.0   \n",
-       "e58gxii                                         2.0   \n",
-       "e64vc8y                                         1.0   \n",
-       "e57504g                                         2.0   \n",
-       "e5borjq                                         1.0   \n",
-       "e64n9zv                                         3.0   \n",
-       "e582ud3                                         1.0   \n",
-       "e64i9cf                                         2.0   \n",
-       "e6q9204                                         2.0   \n",
-       "e5modd7                                         1.0   \n",
-       "e5xhbyd                                         3.0   \n",
-       "e5oaf7h                                         3.0   \n",
-       "e6nir3u                                         4.0   \n",
-       "e6c3xdn                                         1.0   \n",
-       "e5d3zaa                                         2.0   \n",
-       "e5gnjv9                                         1.0   \n",
-       "e69gw2t                                         3.0   \n",
-       "e5syrih                                         2.0   \n",
-       "e5sa2yf                                         4.0   \n",
-       "e6ai7z5                                         1.0   \n",
+       "         prop-nonzero[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                         0.7   \n",
+       "e5ytz1d                                         0.4   \n",
+       "e6ls80j                                         0.4   \n",
+       "e5mhgl5                                         0.7   \n",
+       "e6w6fah                                         0.1   \n",
        "...                                             ...   \n",
-       "e5smhzk                                         4.0   \n",
-       "e5v91s0                                         1.0   \n",
-       "e6n6di6                                         1.0   \n",
-       "e6iqq30                                         1.0   \n",
-       "e5bfad7                                         1.0   \n",
-       "e6x5he5                                         1.0   \n",
-       "e6l9uyf                                         1.0   \n",
-       "e57hyr1                                         2.0   \n",
-       "e5b8sj7                                         1.0   \n",
-       "e6nlep7                                         1.0   \n",
-       "e6ltazd                                         3.0   \n",
-       "e57a6qq                                         3.0   \n",
-       "e5qc7eb                                         2.0   \n",
-       "e6hqt5y                                         1.0   \n",
-       "e5ua84v                                         2.0   \n",
-       "e65m7kq                                         1.0   \n",
-       "e5ggtru                                         1.0   \n",
-       "e5pmmig                                         3.0   \n",
-       "e64l6vq                                         2.0   \n",
-       "e6fjx0d                                         4.0   \n",
-       "e5h3xyy                                         1.0   \n",
-       "e589ri5                                         1.0   \n",
-       "e5beuqa                                         2.0   \n",
-       "e5lqoj1                                         2.0   \n",
-       "e5kvch1                                         2.0   \n",
-       "e6srvwm                                         1.0   \n",
-       "e5o65mk                                         4.0   \n",
-       "e647cm8                                         1.0   \n",
-       "e58n526                                         1.0   \n",
-       "e69r2kg                                         1.0   \n",
+       "e65ca8k                                         0.8   \n",
+       "e6cdkpy                                         0.4   \n",
+       "e5wc4tj                                         0.9   \n",
+       "e6ua0sb                                         0.5   \n",
+       "e5ua84v                                         0.6   \n",
        "\n",
-       "         argmax[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                              1.0   \n",
-       "e5ywqyk                                              0.0   \n",
-       "e5qv9rj                                              2.0   \n",
-       "e6jhojf                                              1.0   \n",
-       "e6989ii                                              0.0   \n",
-       "e69lgse                                              1.0   \n",
-       "e5kwkg2                                              0.0   \n",
-       "e6mehe7                                              1.0   \n",
-       "e6m0hsd                                              0.0   \n",
-       "e64r385                                              1.0   \n",
-       "e5surbt                                              0.0   \n",
-       "e58gxii                                              1.0   \n",
-       "e64vc8y                                              0.0   \n",
-       "e57504g                                              0.0   \n",
-       "e5borjq                                              3.0   \n",
-       "e64n9zv                                              0.0   \n",
-       "e582ud3                                              0.0   \n",
-       "e64i9cf                                              2.0   \n",
-       "e6q9204                                              0.0   \n",
-       "e5modd7                                              1.0   \n",
-       "e5xhbyd                                              0.0   \n",
-       "e5oaf7h                                              0.0   \n",
-       "e6nir3u                                              0.0   \n",
-       "e6c3xdn                                              0.0   \n",
-       "e5d3zaa                                              0.0   \n",
-       "e5gnjv9                                              2.0   \n",
-       "e69gw2t                                              0.0   \n",
-       "e5syrih                                              0.0   \n",
-       "e5sa2yf                                              0.0   \n",
-       "e6ai7z5                                              0.0   \n",
+       "         prop-multiple[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                      0.800000   \n",
+       "e5ytz1d                                      0.000000   \n",
+       "e6ls80j                                      0.333333   \n",
+       "e5mhgl5                                      0.285714   \n",
+       "e6w6fah                                      0.000000   \n",
+       "...                                               ...   \n",
+       "e65ca8k                                      0.500000   \n",
+       "e6cdkpy                                      0.000000   \n",
+       "e5wc4tj                                      1.000000   \n",
+       "e6ua0sb                                      0.600000   \n",
+       "e5ua84v                                      0.333333   \n",
+       "\n",
+       "         prop-multiple[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                     0.142857   \n",
+       "e5ytz1d                                     0.750000   \n",
+       "e6ls80j                                     0.500000   \n",
+       "e5mhgl5                                     0.285714   \n",
+       "e6w6fah                                     1.000000   \n",
+       "...                                              ...   \n",
+       "e65ca8k                                     0.125000   \n",
+       "e6cdkpy                                     0.750000   \n",
+       "e5wc4tj                                     0.000000   \n",
+       "e6ua0sb                                     0.400000   \n",
+       "e5ua84v                                     0.333333   \n",
+       "\n",
+       "         entropy[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                1.581094   \n",
+       "e5ytz1d                                2.197225   \n",
+       "e6ls80j                                1.676988   \n",
+       "e5mhgl5                                1.889159   \n",
+       "e6w6fah                                2.079442   \n",
+       "...                                         ...   \n",
+       "e65ca8k                                0.348832   \n",
+       "e6cdkpy                                2.197225   \n",
+       "e5wc4tj                                0.686962   \n",
+       "e6ua0sb                                1.522955   \n",
+       "e5ua84v                                1.676988   \n",
+       "\n",
+       "         entropy[indegree over C->c responses]  \\\n",
+       "e5hm9mp                               1.831020   \n",
+       "e5ytz1d                               1.310784   \n",
+       "e6ls80j                               1.214890   \n",
+       "e5mhgl5                               1.889159   \n",
+       "e6w6fah                               0.000000   \n",
+       "...                                        ...   \n",
+       "e65ca8k                               2.043192   \n",
+       "e6cdkpy                               1.273028   \n",
+       "e5wc4tj                               2.197225   \n",
+       "e6ua0sb                               1.427061   \n",
+       "e5ua84v                               1.676988   \n",
+       "\n",
+       "         2nd-largest / max[outdegree over C->c responses]  \\\n",
+       "e5hm9mp                                          1.000000   \n",
+       "e5ytz1d                                          1.000000   \n",
+       "e6ls80j                                          0.666667   \n",
+       "e5mhgl5                                          1.000000   \n",
+       "e6w6fah                                          1.000000   \n",
+       "...                                                   ...   \n",
+       "e65ca8k                                          0.125000   \n",
+       "e6cdkpy                                          1.000000   \n",
+       "e5wc4tj                                          0.800000   \n",
+       "e6ua0sb                                          0.666667   \n",
+       "e5ua84v                                          0.666667   \n",
+       "\n",
+       "         2nd-largest / max[indegree over C->c responses]  \\\n",
+       "e5hm9mp                                         0.333333   \n",
+       "e5ytz1d                                         1.000000   \n",
+       "e6ls80j                                         0.750000   \n",
+       "e5mhgl5                                         1.000000   \n",
+       "e6w6fah                                         0.000000   \n",
        "...                                                  ...   \n",
-       "e5smhzk                                              0.0   \n",
-       "e5v91s0                                              1.0   \n",
-       "e6n6di6                                              1.0   \n",
-       "e6iqq30                                              0.0   \n",
-       "e5bfad7                                              0.0   \n",
-       "e6x5he5                                              0.0   \n",
-       "e6l9uyf                                              2.0   \n",
-       "e57hyr1                                              4.0   \n",
-       "e5b8sj7                                              0.0   \n",
-       "e6nlep7                                              0.0   \n",
-       "e6ltazd                                              0.0   \n",
-       "e57a6qq                                              0.0   \n",
-       "e5qc7eb                                              1.0   \n",
-       "e6hqt5y                                              0.0   \n",
-       "e5ua84v                                              0.0   \n",
-       "e65m7kq                                              1.0   \n",
-       "e5ggtru                                              0.0   \n",
-       "e5pmmig                                              0.0   \n",
-       "e64l6vq                                              2.0   \n",
-       "e6fjx0d                                              0.0   \n",
-       "e5h3xyy                                              4.0   \n",
-       "e589ri5                                              1.0   \n",
-       "e5beuqa                                              1.0   \n",
-       "e5lqoj1                                              0.0   \n",
-       "e5kvch1                                              3.0   \n",
-       "e6srvwm                                              0.0   \n",
-       "e5o65mk                                              0.0   \n",
-       "e647cm8                                              0.0   \n",
-       "e58n526                                              0.0   \n",
-       "e69r2kg                                              2.0   \n",
+       "e65ca8k                                         0.500000   \n",
+       "e6cdkpy                                         0.500000   \n",
+       "e5wc4tj                                         1.000000   \n",
+       "e6ua0sb                                         0.500000   \n",
+       "e5ua84v                                         0.666667   \n",
+       "\n",
+       "         max[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                 2.0   \n",
+       "e5ytz1d                                 1.0   \n",
+       "e6ls80j                                 3.0   \n",
+       "e5mhgl5                                 2.0   \n",
+       "e6w6fah                                 1.0   \n",
+       "...                                     ...   \n",
+       "e65ca8k                                 1.0   \n",
+       "e6cdkpy                                 1.0   \n",
+       "e5wc4tj                                 1.0   \n",
+       "e6ua0sb                                 2.0   \n",
+       "e5ua84v                                 3.0   \n",
+       "\n",
+       "         max[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                3.0   \n",
+       "e5ytz1d                                3.0   \n",
+       "e6ls80j                                4.0   \n",
+       "e5mhgl5                                2.0   \n",
+       "e6w6fah                                8.0   \n",
+       "...                                    ...   \n",
+       "e65ca8k                                2.0   \n",
+       "e6cdkpy                                4.0   \n",
+       "e5wc4tj                                1.0   \n",
+       "e6ua0sb                                4.0   \n",
+       "e5ua84v                                4.0   \n",
+       "\n",
+       "         argmax[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                    0.0   \n",
+       "e5ytz1d                                    0.0   \n",
+       "e6ls80j                                    3.0   \n",
+       "e5mhgl5                                    4.0   \n",
+       "e6w6fah                                    1.0   \n",
+       "...                                        ...   \n",
+       "e65ca8k                                    0.0   \n",
+       "e6cdkpy                                    1.0   \n",
+       "e5wc4tj                                    0.0   \n",
+       "e6ua0sb                                    2.0   \n",
+       "e5ua84v                                    1.0   \n",
        "\n",
        "         argmax[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                   0.0   \n",
-       "e5ywqyk                                   0.0   \n",
-       "e5qv9rj                                   0.0   \n",
-       "e6jhojf                                   0.0   \n",
-       "e6989ii                                   0.0   \n",
-       "e69lgse                                   0.0   \n",
-       "e5kwkg2                                   0.0   \n",
-       "e6mehe7                                   0.0   \n",
-       "e6m0hsd                                   1.0   \n",
-       "e64r385                                   0.0   \n",
-       "e5surbt                                   0.0   \n",
-       "e58gxii                                   0.0   \n",
-       "e64vc8y                                   0.0   \n",
-       "e57504g                                   0.0   \n",
-       "e5borjq                                   4.0   \n",
-       "e64n9zv                                   1.0   \n",
-       "e582ud3                                   0.0   \n",
-       "e64i9cf                                   0.0   \n",
-       "e6q9204                                   1.0   \n",
-       "e5modd7                                   2.0   \n",
-       "e5xhbyd                                   0.0   \n",
-       "e5oaf7h                                   1.0   \n",
-       "e6nir3u                                   0.0   \n",
-       "e6c3xdn                                   1.0   \n",
-       "e5d3zaa                                   0.0   \n",
-       "e5gnjv9                                   0.0   \n",
-       "e69gw2t                                   0.0   \n",
-       "e5syrih                                   1.0   \n",
-       "e5sa2yf                                   0.0   \n",
-       "e6ai7z5                                   0.0   \n",
+       "e5hm9mp                                   1.0   \n",
+       "e5ytz1d                                   0.0   \n",
+       "e6ls80j                                   0.0   \n",
+       "e5mhgl5                                   1.0   \n",
+       "e6w6fah                                   0.0   \n",
        "...                                       ...   \n",
-       "e5smhzk                                   0.0   \n",
-       "e5v91s0                                   0.0   \n",
-       "e6n6di6                                   2.0   \n",
-       "e6iqq30                                   0.0   \n",
-       "e5bfad7                                   0.0   \n",
-       "e6x5he5                                   0.0   \n",
-       "e6l9uyf                                   0.0   \n",
-       "e57hyr1                                   0.0   \n",
-       "e5b8sj7                                   1.0   \n",
-       "e6nlep7                                   0.0   \n",
-       "e6ltazd                                   1.0   \n",
-       "e57a6qq                                   1.0   \n",
-       "e5qc7eb                                   0.0   \n",
-       "e6hqt5y                                   0.0   \n",
+       "e65ca8k                                   0.0   \n",
+       "e6cdkpy                                   0.0   \n",
+       "e5wc4tj                                   0.0   \n",
+       "e6ua0sb                                   0.0   \n",
        "e5ua84v                                   1.0   \n",
-       "e65m7kq                                   0.0   \n",
-       "e5ggtru                                   1.0   \n",
-       "e5pmmig                                   1.0   \n",
-       "e64l6vq                                   0.0   \n",
-       "e6fjx0d                                   0.0   \n",
-       "e5h3xyy                                   0.0   \n",
-       "e589ri5                                   0.0   \n",
-       "e5beuqa                                   2.0   \n",
-       "e5lqoj1                                   0.0   \n",
-       "e5kvch1                                   0.0   \n",
-       "e6srvwm                                   0.0   \n",
-       "e5o65mk                                   0.0   \n",
-       "e647cm8                                   0.0   \n",
-       "e58n526                                   0.0   \n",
-       "e69r2kg                                   2.0   \n",
        "\n",
-       "         argmax[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                              0.0   \n",
-       "e5ywqyk                                              0.0   \n",
-       "e5qv9rj                                              2.0   \n",
-       "e6jhojf                                              3.0   \n",
-       "e6989ii                                              0.0   \n",
-       "e69lgse                                              1.0   \n",
-       "e5kwkg2                                              0.0   \n",
-       "e6mehe7                                              1.0   \n",
-       "e6m0hsd                                              0.0   \n",
-       "e64r385                                              1.0   \n",
-       "e5surbt                                              0.0   \n",
-       "e58gxii                                              1.0   \n",
-       "e64vc8y                                              0.0   \n",
-       "e57504g                                              0.0   \n",
-       "e5borjq                                              3.0   \n",
-       "e64n9zv                                              2.0   \n",
-       "e582ud3                                              0.0   \n",
-       "e64i9cf                                              2.0   \n",
-       "e6q9204                                              0.0   \n",
-       "e5modd7                                              1.0   \n",
-       "e5xhbyd                                              0.0   \n",
-       "e5oaf7h                                              0.0   \n",
-       "e6nir3u                                              0.0   \n",
-       "e6c3xdn                                              0.0   \n",
-       "e5d3zaa                                              0.0   \n",
-       "e5gnjv9                                              2.0   \n",
-       "e69gw2t                                              0.0   \n",
-       "e5syrih                                              0.0   \n",
-       "e5sa2yf                                              0.0   \n",
-       "e6ai7z5                                              0.0   \n",
-       "...                                                  ...   \n",
-       "e5smhzk                                              0.0   \n",
-       "e5v91s0                                              1.0   \n",
-       "e6n6di6                                              5.0   \n",
-       "e6iqq30                                              0.0   \n",
-       "e5bfad7                                              0.0   \n",
-       "e6x5he5                                              0.0   \n",
-       "e6l9uyf                                              3.0   \n",
-       "e57hyr1                                              4.0   \n",
-       "e5b8sj7                                              0.0   \n",
-       "e6nlep7                                              0.0   \n",
-       "e6ltazd                                              0.0   \n",
-       "e57a6qq                                              1.0   \n",
-       "e5qc7eb                                              3.0   \n",
-       "e6hqt5y                                              0.0   \n",
-       "e5ua84v                                              0.0   \n",
-       "e65m7kq                                              1.0   \n",
-       "e5ggtru                                              0.0   \n",
-       "e5pmmig                                              0.0   \n",
-       "e64l6vq                                              4.0   \n",
-       "e6fjx0d                                              0.0   \n",
-       "e5h3xyy                                              4.0   \n",
-       "e589ri5                                              1.0   \n",
-       "e5beuqa                                              1.0   \n",
-       "e5lqoj1                                              0.0   \n",
-       "e5kvch1                                              1.0   \n",
-       "e6srvwm                                              0.0   \n",
-       "e5o65mk                                              0.0   \n",
-       "e647cm8                                              0.0   \n",
-       "e58n526                                              0.0   \n",
-       "e69r2kg                                              0.0   \n",
+       "         norm.max[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                 0.250000   \n",
+       "e5ytz1d                                 0.111111   \n",
+       "e6ls80j                                 0.333333   \n",
+       "e5mhgl5                                 0.250000   \n",
+       "e6w6fah                                 0.125000   \n",
+       "...                                          ...   \n",
+       "e65ca8k                                 0.500000   \n",
+       "e6cdkpy                                 0.111111   \n",
+       "e5wc4tj                                 0.500000   \n",
+       "e6ua0sb                                 0.285714   \n",
+       "e5ua84v                                 0.333333   \n",
        "\n",
-       "         argmax[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                   0.0   \n",
-       "e5ywqyk                                   1.0   \n",
-       "e5qv9rj                                   0.0   \n",
-       "e6jhojf                                   4.0   \n",
-       "e6989ii                                   0.0   \n",
-       "e69lgse                                   0.0   \n",
-       "e5kwkg2                                   0.0   \n",
-       "e6mehe7                                   0.0   \n",
-       "e6m0hsd                                   1.0   \n",
-       "e64r385                                   0.0   \n",
-       "e5surbt                                   0.0   \n",
-       "e58gxii                                   0.0   \n",
-       "e64vc8y                                   0.0   \n",
-       "e57504g                                   0.0   \n",
-       "e5borjq                                   4.0   \n",
-       "e64n9zv                                   3.0   \n",
-       "e582ud3                                   0.0   \n",
-       "e64i9cf                                   0.0   \n",
-       "e6q9204                                   1.0   \n",
-       "e5modd7                                   2.0   \n",
-       "e5xhbyd                                   1.0   \n",
-       "e5oaf7h                                   1.0   \n",
-       "e6nir3u                                   0.0   \n",
-       "e6c3xdn                                   1.0   \n",
-       "e5d3zaa                                   0.0   \n",
-       "e5gnjv9                                   0.0   \n",
-       "e69gw2t                                   0.0   \n",
-       "e5syrih                                   1.0   \n",
-       "e5sa2yf                                   0.0   \n",
-       "e6ai7z5                                   0.0   \n",
-       "...                                       ...   \n",
-       "e5smhzk                                   0.0   \n",
-       "e5v91s0                                   0.0   \n",
-       "e6n6di6                                   6.0   \n",
-       "e6iqq30                                   0.0   \n",
-       "e5bfad7                                   0.0   \n",
-       "e6x5he5                                   0.0   \n",
-       "e6l9uyf                                   0.0   \n",
-       "e57hyr1                                   0.0   \n",
-       "e5b8sj7                                   0.0   \n",
-       "e6nlep7                                   0.0   \n",
-       "e6ltazd                                   1.0   \n",
-       "e57a6qq                                   2.0   \n",
-       "e5qc7eb                                   4.0   \n",
-       "e6hqt5y                                   0.0   \n",
-       "e5ua84v                                   1.0   \n",
-       "e65m7kq                                   0.0   \n",
-       "e5ggtru                                   1.0   \n",
-       "e5pmmig                                   1.0   \n",
-       "e64l6vq                                   0.0   \n",
-       "e6fjx0d                                   0.0   \n",
-       "e5h3xyy                                   0.0   \n",
-       "e589ri5                                   0.0   \n",
-       "e5beuqa                                   2.0   \n",
-       "e5lqoj1                                   0.0   \n",
-       "e5kvch1                                   0.0   \n",
-       "e6srvwm                                   0.0   \n",
-       "e5o65mk                                   0.0   \n",
-       "e647cm8                                   0.0   \n",
-       "e58n526                                   0.0   \n",
-       "e69r2kg                                   0.0   \n",
+       "         norm.max[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                0.375000   \n",
+       "e5ytz1d                                0.333333   \n",
+       "e6ls80j                                0.444444   \n",
+       "e5mhgl5                                0.250000   \n",
+       "e6w6fah                                1.000000   \n",
+       "...                                         ...   \n",
+       "e65ca8k                                1.000000   \n",
+       "e6cdkpy                                0.444444   \n",
+       "e5wc4tj                                0.500000   \n",
+       "e6ua0sb                                0.571429   \n",
+       "e5ua84v                                0.444444   \n",
        "\n",
-       "         argmax[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                              0.0   \n",
-       "e5ywqyk                                              0.0   \n",
-       "e5qv9rj                                              2.0   \n",
-       "e6jhojf                                              3.0   \n",
-       "e6989ii                                              5.0   \n",
-       "e69lgse                                              1.0   \n",
-       "e5kwkg2                                              0.0   \n",
-       "e6mehe7                                              1.0   \n",
-       "e6m0hsd                                              0.0   \n",
-       "e64r385                                              1.0   \n",
-       "e5surbt                                              0.0   \n",
-       "e58gxii                                              1.0   \n",
-       "e64vc8y                                              0.0   \n",
-       "e57504g                                              0.0   \n",
-       "e5borjq                                              3.0   \n",
-       "e64n9zv                                              2.0   \n",
-       "e582ud3                                              0.0   \n",
-       "e64i9cf                                              2.0   \n",
-       "e6q9204                                              0.0   \n",
-       "e5modd7                                              1.0   \n",
-       "e5xhbyd                                              0.0   \n",
-       "e5oaf7h                                              0.0   \n",
-       "e6nir3u                                              6.0   \n",
-       "e6c3xdn                                              0.0   \n",
-       "e5d3zaa                                              0.0   \n",
-       "e5gnjv9                                              2.0   \n",
-       "e69gw2t                                              0.0   \n",
-       "e5syrih                                              0.0   \n",
-       "e5sa2yf                                              0.0   \n",
-       "e6ai7z5                                              0.0   \n",
+       "         2nd-largest[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                         2.0   \n",
+       "e5ytz1d                                         1.0   \n",
+       "e6ls80j                                         2.0   \n",
+       "e5mhgl5                                         1.0   \n",
+       "e6w6fah                                         1.0   \n",
+       "...                                             ...   \n",
+       "e65ca8k                                         1.0   \n",
+       "e6cdkpy                                         1.0   \n",
+       "e5wc4tj                                         1.0   \n",
+       "e6ua0sb                                         2.0   \n",
+       "e5ua84v                                         2.0   \n",
+       "\n",
+       "         2nd-largest[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                        2.0   \n",
+       "e5ytz1d                                        3.0   \n",
+       "e6ls80j                                        3.0   \n",
+       "e5mhgl5                                        2.0   \n",
+       "e6w6fah                                        0.0   \n",
+       "...                                            ...   \n",
+       "e65ca8k                                        0.0   \n",
+       "e6cdkpy                                        2.0   \n",
+       "e5wc4tj                                        1.0   \n",
+       "e6ua0sb                                        1.0   \n",
+       "e5ua84v                                        2.0   \n",
+       "\n",
+       "         2nd-argmax[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                        2.0   \n",
+       "e5ytz1d                                        1.0   \n",
+       "e6ls80j                                        2.0   \n",
+       "e5mhgl5                                        1.0   \n",
+       "e6w6fah                                        2.0   \n",
+       "...                                            ...   \n",
+       "e65ca8k                                        1.0   \n",
+       "e6cdkpy                                        2.0   \n",
+       "e5wc4tj                                        1.0   \n",
+       "e6ua0sb                                        4.0   \n",
+       "e5ua84v                                        4.0   \n",
+       "\n",
+       "         2nd-argmax[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                       0.0   \n",
+       "e5ytz1d                                       2.0   \n",
+       "e6ls80j                                       2.0   \n",
+       "e5mhgl5                                       4.0   \n",
+       "e6w6fah                                       1.0   \n",
+       "...                                           ...   \n",
+       "e65ca8k                                       1.0   \n",
+       "e6cdkpy                                       1.0   \n",
+       "e5wc4tj                                       1.0   \n",
+       "e6ua0sb                                       1.0   \n",
+       "e5ua84v                                       4.0   \n",
+       "\n",
+       "         norm.2nd-largest[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                         0.250000   \n",
+       "e5ytz1d                                         0.111111   \n",
+       "e6ls80j                                         0.222222   \n",
+       "e5mhgl5                                         0.125000   \n",
+       "e6w6fah                                         0.125000   \n",
        "...                                                  ...   \n",
-       "e5smhzk                                              0.0   \n",
-       "e5v91s0                                              1.0   \n",
-       "e6n6di6                                              5.0   \n",
-       "e6iqq30                                              0.0   \n",
-       "e5bfad7                                              0.0   \n",
-       "e6x5he5                                              3.0   \n",
-       "e6l9uyf                                              3.0   \n",
-       "e57hyr1                                              4.0   \n",
-       "e5b8sj7                                              0.0   \n",
-       "e6nlep7                                              0.0   \n",
-       "e6ltazd                                              0.0   \n",
-       "e57a6qq                                              1.0   \n",
-       "e5qc7eb                                              3.0   \n",
-       "e6hqt5y                                              0.0   \n",
-       "e5ua84v                                              0.0   \n",
-       "e65m7kq                                              1.0   \n",
-       "e5ggtru                                              0.0   \n",
-       "e5pmmig                                              0.0   \n",
-       "e64l6vq                                              4.0   \n",
-       "e6fjx0d                                              0.0   \n",
-       "e5h3xyy                                              4.0   \n",
-       "e589ri5                                              1.0   \n",
-       "e5beuqa                                              1.0   \n",
-       "e5lqoj1                                              0.0   \n",
-       "e5kvch1                                              1.0   \n",
-       "e6srvwm                                              0.0   \n",
-       "e5o65mk                                              0.0   \n",
-       "e647cm8                                              0.0   \n",
-       "e58n526                                              0.0   \n",
-       "e69r2kg                                              0.0   \n",
+       "e65ca8k                                         0.500000   \n",
+       "e6cdkpy                                         0.111111   \n",
+       "e5wc4tj                                         0.500000   \n",
+       "e6ua0sb                                         0.285714   \n",
+       "e5ua84v                                         0.222222   \n",
        "\n",
-       "         argmax[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                   0.0   \n",
-       "e5ywqyk                                   1.0   \n",
-       "e5qv9rj                                   0.0   \n",
-       "e6jhojf                                   4.0   \n",
-       "e6989ii                                   6.0   \n",
-       "e69lgse                                   0.0   \n",
-       "e5kwkg2                                   0.0   \n",
-       "e6mehe7                                   0.0   \n",
-       "e6m0hsd                                   1.0   \n",
-       "e64r385                                   0.0   \n",
-       "e5surbt                                   0.0   \n",
-       "e58gxii                                   0.0   \n",
-       "e64vc8y                                   0.0   \n",
-       "e57504g                                   0.0   \n",
-       "e5borjq                                   4.0   \n",
-       "e64n9zv                                   3.0   \n",
-       "e582ud3                                   0.0   \n",
-       "e64i9cf                                   0.0   \n",
-       "e6q9204                                   1.0   \n",
-       "e5modd7                                   2.0   \n",
-       "e5xhbyd                                   1.0   \n",
-       "e5oaf7h                                   1.0   \n",
-       "e6nir3u                                   7.0   \n",
-       "e6c3xdn                                   1.0   \n",
-       "e5d3zaa                                   0.0   \n",
-       "e5gnjv9                                   0.0   \n",
-       "e69gw2t                                   0.0   \n",
-       "e5syrih                                   1.0   \n",
-       "e5sa2yf                                   0.0   \n",
-       "e6ai7z5                                   0.0   \n",
-       "...                                       ...   \n",
-       "e5smhzk                                   0.0   \n",
-       "e5v91s0                                   0.0   \n",
-       "e6n6di6                                   6.0   \n",
-       "e6iqq30                                   0.0   \n",
-       "e5bfad7                                   0.0   \n",
-       "e6x5he5                                   0.0   \n",
-       "e6l9uyf                                   0.0   \n",
-       "e57hyr1                                   0.0   \n",
-       "e5b8sj7                                   0.0   \n",
-       "e6nlep7                                   0.0   \n",
-       "e6ltazd                                   1.0   \n",
-       "e57a6qq                                   2.0   \n",
-       "e5qc7eb                                   4.0   \n",
-       "e6hqt5y                                   0.0   \n",
-       "e5ua84v                                   1.0   \n",
-       "e65m7kq                                   0.0   \n",
-       "e5ggtru                                   1.0   \n",
-       "e5pmmig                                   1.0   \n",
-       "e64l6vq                                   0.0   \n",
-       "e6fjx0d                                   0.0   \n",
-       "e5h3xyy                                   0.0   \n",
-       "e589ri5                                   0.0   \n",
-       "e5beuqa                                   2.0   \n",
-       "e5lqoj1                                   0.0   \n",
-       "e5kvch1                                   0.0   \n",
-       "e6srvwm                                   0.0   \n",
-       "e5o65mk                                   0.0   \n",
-       "e647cm8                                   0.0   \n",
-       "e58n526                                   0.0   \n",
-       "e69r2kg                                   0.0   \n",
+       "         norm.2nd-largest[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                        0.250000   \n",
+       "e5ytz1d                                        0.333333   \n",
+       "e6ls80j                                        0.333333   \n",
+       "e5mhgl5                                        0.250000   \n",
+       "e6w6fah                                        0.000000   \n",
+       "...                                                 ...   \n",
+       "e65ca8k                                        0.000000   \n",
+       "e6cdkpy                                        0.222222   \n",
+       "e5wc4tj                                        0.500000   \n",
+       "e6ua0sb                                        0.142857   \n",
+       "e5ua84v                                        0.222222   \n",
        "\n",
-       "         argmax[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                               1.0   \n",
-       "e5ywqyk                                               1.0   \n",
-       "e5qv9rj                                               2.0   \n",
-       "e6jhojf                                               1.0   \n",
-       "e6989ii                                               0.0   \n",
-       "e69lgse                                               2.0   \n",
-       "e5kwkg2                                               1.0   \n",
-       "e6mehe7                                               2.0   \n",
-       "e6m0hsd                                               0.0   \n",
-       "e64r385                                               2.0   \n",
-       "e5surbt                                               1.0   \n",
-       "e58gxii                                               1.0   \n",
-       "e64vc8y                                               3.0   \n",
-       "e57504g                                               5.0   \n",
-       "e5borjq                                               1.0   \n",
-       "e64n9zv                                               0.0   \n",
-       "e582ud3                                               4.0   \n",
-       "e64i9cf                                               1.0   \n",
-       "e6q9204                                               0.0   \n",
-       "e5modd7                                               1.0   \n",
-       "e5xhbyd                                               0.0   \n",
-       "e5oaf7h                                               0.0   \n",
-       "e6nir3u                                               0.0   \n",
-       "e6c3xdn                                               1.0   \n",
-       "e5d3zaa                                               0.0   \n",
-       "e5gnjv9                                               6.0   \n",
-       "e69gw2t                                               2.0   \n",
-       "e5syrih                                               3.0   \n",
-       "e5sa2yf                                               0.0   \n",
-       "e6ai7z5                                               0.0   \n",
-       "...                                                   ...   \n",
-       "e5smhzk                                               1.0   \n",
-       "e5v91s0                                               3.0   \n",
-       "e6n6di6                                               1.0   \n",
-       "e6iqq30                                               4.0   \n",
-       "e5bfad7                                               2.0   \n",
-       "e6x5he5                                               1.0   \n",
-       "e6l9uyf                                               2.0   \n",
-       "e57hyr1                                               1.0   \n",
-       "e5b8sj7                                               0.0   \n",
-       "e6nlep7                                               0.0   \n",
-       "e6ltazd                                               0.0   \n",
-       "e57a6qq                                               1.0   \n",
-       "e5qc7eb                                               0.0   \n",
-       "e6hqt5y                                               1.0   \n",
-       "e5ua84v                                               0.0   \n",
-       "e65m7kq                                               1.0   \n",
-       "e5ggtru                                               0.0   \n",
-       "e5pmmig                                               0.0   \n",
-       "e64l6vq                                               1.0   \n",
-       "e6fjx0d                                               0.0   \n",
-       "e5h3xyy                                               2.0   \n",
-       "e589ri5                                               4.0   \n",
-       "e5beuqa                                               1.0   \n",
-       "e5lqoj1                                               4.0   \n",
-       "e5kvch1                                               1.0   \n",
-       "e6srvwm                                               0.0   \n",
-       "e5o65mk                                               0.0   \n",
-       "e647cm8                                               1.0   \n",
-       "e58n526                                               0.0   \n",
-       "e69r2kg                                               2.0   \n",
+       "         mean[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                             1.600000   \n",
+       "e5ytz1d                             1.000000   \n",
+       "e6ls80j                             1.285714   \n",
+       "e5mhgl5                             1.000000   \n",
+       "e6w6fah                             0.888889   \n",
+       "...                                      ...   \n",
+       "e65ca8k                             1.000000   \n",
+       "e6cdkpy                             0.900000   \n",
+       "e5wc4tj                             1.000000   \n",
+       "e6ua0sb                             1.400000   \n",
+       "e5ua84v                             1.285714   \n",
        "\n",
-       "         argmax[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                    0.0   \n",
-       "e5ywqyk                                    0.0   \n",
-       "e5qv9rj                                    1.0   \n",
-       "e6jhojf                                    0.0   \n",
-       "e6989ii                                    0.0   \n",
-       "e69lgse                                    0.0   \n",
-       "e5kwkg2                                    1.0   \n",
-       "e6mehe7                                    0.0   \n",
-       "e6m0hsd                                    1.0   \n",
-       "e64r385                                    2.0   \n",
-       "e5surbt                                    1.0   \n",
-       "e58gxii                                    0.0   \n",
-       "e64vc8y                                    1.0   \n",
-       "e57504g                                    5.0   \n",
-       "e5borjq                                    4.0   \n",
-       "e64n9zv                                    1.0   \n",
-       "e582ud3                                    1.0   \n",
-       "e64i9cf                                    0.0   \n",
-       "e6q9204                                    1.0   \n",
-       "e5modd7                                    1.0   \n",
-       "e5xhbyd                                    0.0   \n",
-       "e5oaf7h                                    1.0   \n",
-       "e6nir3u                                    0.0   \n",
-       "e6c3xdn                                    1.0   \n",
-       "e5d3zaa                                    1.0   \n",
-       "e5gnjv9                                    7.0   \n",
-       "e69gw2t                                    1.0   \n",
-       "e5syrih                                    1.0   \n",
-       "e5sa2yf                                    0.0   \n",
-       "e6ai7z5                                    1.0   \n",
-       "...                                        ...   \n",
-       "e5smhzk                                    0.0   \n",
-       "e5v91s0                                    1.0   \n",
-       "e6n6di6                                    2.0   \n",
-       "e6iqq30                                    0.0   \n",
-       "e5bfad7                                    0.0   \n",
-       "e6x5he5                                    0.0   \n",
-       "e6l9uyf                                    3.0   \n",
-       "e57hyr1                                    2.0   \n",
-       "e5b8sj7                                    1.0   \n",
-       "e6nlep7                                    1.0   \n",
-       "e6ltazd                                    1.0   \n",
-       "e57a6qq                                    0.0   \n",
-       "e5qc7eb                                    1.0   \n",
-       "e6hqt5y                                    4.0   \n",
-       "e5ua84v                                    1.0   \n",
-       "e65m7kq                                    2.0   \n",
-       "e5ggtru                                    1.0   \n",
-       "e5pmmig                                    1.0   \n",
-       "e64l6vq                                    0.0   \n",
-       "e6fjx0d                                    1.0   \n",
-       "e5h3xyy                                    5.0   \n",
-       "e589ri5                                    1.0   \n",
-       "e5beuqa                                    2.0   \n",
-       "e5lqoj1                                    5.0   \n",
-       "e5kvch1                                    2.0   \n",
-       "e6srvwm                                    1.0   \n",
-       "e5o65mk                                    0.0   \n",
-       "e647cm8                                    0.0   \n",
-       "e58n526                                    1.0   \n",
-       "e69r2kg                                    2.0   \n",
+       "         mean[indegree over C->C responses]  \\\n",
+       "e5hm9mp                            1.600000   \n",
+       "e5ytz1d                            1.000000   \n",
+       "e6ls80j                            1.285714   \n",
+       "e5mhgl5                            1.000000   \n",
+       "e6w6fah                            0.888889   \n",
+       "...                                     ...   \n",
+       "e65ca8k                            1.000000   \n",
+       "e6cdkpy                            0.900000   \n",
+       "e5wc4tj                            1.000000   \n",
+       "e6ua0sb                            1.400000   \n",
+       "e5ua84v                            1.285714   \n",
        "\n",
-       "         argmax[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                               1.0   \n",
-       "e5ywqyk                                               1.0   \n",
-       "e5qv9rj                                               2.0   \n",
-       "e6jhojf                                               1.0   \n",
-       "e6989ii                                               1.0   \n",
-       "e69lgse                                               2.0   \n",
-       "e5kwkg2                                               1.0   \n",
-       "e6mehe7                                               2.0   \n",
-       "e6m0hsd                                               0.0   \n",
-       "e64r385                                               2.0   \n",
-       "e5surbt                                               1.0   \n",
-       "e58gxii                                               1.0   \n",
-       "e64vc8y                                               3.0   \n",
-       "e57504g                                               5.0   \n",
-       "e5borjq                                               1.0   \n",
-       "e64n9zv                                               0.0   \n",
-       "e582ud3                                               4.0   \n",
-       "e64i9cf                                               1.0   \n",
-       "e6q9204                                               0.0   \n",
-       "e5modd7                                               1.0   \n",
-       "e5xhbyd                                               1.0   \n",
-       "e5oaf7h                                               0.0   \n",
-       "e6nir3u                                               1.0   \n",
-       "e6c3xdn                                               1.0   \n",
-       "e5d3zaa                                               0.0   \n",
-       "e5gnjv9                                               6.0   \n",
-       "e69gw2t                                               2.0   \n",
-       "e5syrih                                               3.0   \n",
-       "e5sa2yf                                               0.0   \n",
-       "e6ai7z5                                               0.0   \n",
-       "...                                                   ...   \n",
-       "e5smhzk                                               1.0   \n",
-       "e5v91s0                                               3.0   \n",
-       "e6n6di6                                               1.0   \n",
-       "e6iqq30                                               4.0   \n",
-       "e5bfad7                                               2.0   \n",
-       "e6x5he5                                               1.0   \n",
-       "e6l9uyf                                               2.0   \n",
-       "e57hyr1                                               1.0   \n",
-       "e5b8sj7                                               0.0   \n",
-       "e6nlep7                                               0.0   \n",
-       "e6ltazd                                               4.0   \n",
-       "e57a6qq                                               1.0   \n",
-       "e5qc7eb                                               2.0   \n",
-       "e6hqt5y                                               1.0   \n",
-       "e5ua84v                                               0.0   \n",
-       "e65m7kq                                               1.0   \n",
-       "e5ggtru                                               0.0   \n",
-       "e5pmmig                                               2.0   \n",
-       "e64l6vq                                               1.0   \n",
-       "e6fjx0d                                               1.0   \n",
-       "e5h3xyy                                               2.0   \n",
-       "e589ri5                                               4.0   \n",
-       "e5beuqa                                               1.0   \n",
-       "e5lqoj1                                               4.0   \n",
-       "e5kvch1                                               2.0   \n",
-       "e6srvwm                                               0.0   \n",
-       "e5o65mk                                               1.0   \n",
-       "e647cm8                                               1.0   \n",
-       "e58n526                                               0.0   \n",
-       "e69r2kg                                               2.0   \n",
+       "         mean-nonzero[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                     1.600000   \n",
+       "e5ytz1d                                     1.000000   \n",
+       "e6ls80j                                     1.500000   \n",
+       "e5mhgl5                                     1.142857   \n",
+       "e6w6fah                                     1.000000   \n",
+       "...                                              ...   \n",
+       "e65ca8k                                     1.000000   \n",
+       "e6cdkpy                                     1.000000   \n",
+       "e5wc4tj                                     1.000000   \n",
+       "e6ua0sb                                     1.400000   \n",
+       "e5ua84v                                     1.500000   \n",
        "\n",
-       "         argmax[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                    0.0   \n",
-       "e5ywqyk                                    0.0   \n",
-       "e5qv9rj                                    1.0   \n",
-       "e6jhojf                                    0.0   \n",
-       "e6989ii                                    0.0   \n",
-       "e69lgse                                    0.0   \n",
-       "e5kwkg2                                    1.0   \n",
-       "e6mehe7                                    0.0   \n",
-       "e6m0hsd                                    1.0   \n",
-       "e64r385                                    2.0   \n",
-       "e5surbt                                    1.0   \n",
-       "e58gxii                                    0.0   \n",
-       "e64vc8y                                    1.0   \n",
-       "e57504g                                    5.0   \n",
-       "e5borjq                                    4.0   \n",
-       "e64n9zv                                    1.0   \n",
-       "e582ud3                                    1.0   \n",
-       "e64i9cf                                    0.0   \n",
-       "e6q9204                                    1.0   \n",
-       "e5modd7                                    1.0   \n",
-       "e5xhbyd                                    0.0   \n",
-       "e5oaf7h                                    1.0   \n",
-       "e6nir3u                                    0.0   \n",
-       "e6c3xdn                                    1.0   \n",
-       "e5d3zaa                                    1.0   \n",
-       "e5gnjv9                                    7.0   \n",
-       "e69gw2t                                    1.0   \n",
-       "e5syrih                                    1.0   \n",
-       "e5sa2yf                                    1.0   \n",
-       "e6ai7z5                                    1.0   \n",
-       "...                                        ...   \n",
-       "e5smhzk                                    0.0   \n",
-       "e5v91s0                                    1.0   \n",
-       "e6n6di6                                    2.0   \n",
-       "e6iqq30                                    0.0   \n",
-       "e5bfad7                                    0.0   \n",
-       "e6x5he5                                    0.0   \n",
-       "e6l9uyf                                    3.0   \n",
-       "e57hyr1                                    2.0   \n",
-       "e5b8sj7                                    1.0   \n",
-       "e6nlep7                                    1.0   \n",
-       "e6ltazd                                    1.0   \n",
-       "e57a6qq                                    0.0   \n",
-       "e5qc7eb                                    0.0   \n",
-       "e6hqt5y                                    4.0   \n",
-       "e5ua84v                                    1.0   \n",
-       "e65m7kq                                    2.0   \n",
-       "e5ggtru                                    1.0   \n",
-       "e5pmmig                                    1.0   \n",
-       "e64l6vq                                    0.0   \n",
-       "e6fjx0d                                    1.0   \n",
-       "e5h3xyy                                    5.0   \n",
-       "e589ri5                                    1.0   \n",
-       "e5beuqa                                    2.0   \n",
-       "e5lqoj1                                    5.0   \n",
-       "e5kvch1                                    2.0   \n",
-       "e6srvwm                                    1.0   \n",
-       "e5o65mk                                    0.0   \n",
-       "e647cm8                                    0.0   \n",
-       "e58n526                                    1.0   \n",
-       "e69r2kg                                    2.0   \n",
+       "         mean-nonzero[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                    1.600000   \n",
+       "e5ytz1d                                    2.250000   \n",
+       "e6ls80j                                    2.250000   \n",
+       "e5mhgl5                                    1.333333   \n",
+       "e6w6fah                                    8.000000   \n",
+       "...                                             ...   \n",
+       "e65ca8k                                    2.000000   \n",
+       "e6cdkpy                                    2.250000   \n",
+       "e5wc4tj                                    1.000000   \n",
+       "e6ua0sb                                    1.750000   \n",
+       "e5ua84v                                    1.800000   \n",
+       "\n",
+       "         prop-nonzero[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                     1.000000   \n",
+       "e5ytz1d                                     1.000000   \n",
+       "e6ls80j                                     0.857143   \n",
+       "e5mhgl5                                     0.875000   \n",
+       "e6w6fah                                     0.888889   \n",
+       "...                                              ...   \n",
+       "e65ca8k                                     1.000000   \n",
+       "e6cdkpy                                     0.900000   \n",
+       "e5wc4tj                                     1.000000   \n",
+       "e6ua0sb                                     1.000000   \n",
+       "e5ua84v                                     0.857143   \n",
        "\n",
-       "         count[dyadic interaction motif over mid-thread]  \\\n",
-       "e6p7yrp                                              2.0   \n",
-       "e5ywqyk                                              1.0   \n",
-       "e5qv9rj                                              0.0   \n",
-       "e6jhojf                                              3.0   \n",
-       "e6989ii                                              1.0   \n",
-       "e69lgse                                              1.0   \n",
-       "e5kwkg2                                              0.0   \n",
-       "e6mehe7                                              1.0   \n",
-       "e6m0hsd                                              2.0   \n",
-       "e64r385                                              2.0   \n",
-       "e5surbt                                              0.0   \n",
-       "e58gxii                                              2.0   \n",
-       "e64vc8y                                              0.0   \n",
-       "e57504g                                              1.0   \n",
-       "e5borjq                                              1.0   \n",
-       "e64n9zv                                              2.0   \n",
-       "e582ud3                                              0.0   \n",
-       "e64i9cf                                              1.0   \n",
-       "e6q9204                                              2.0   \n",
-       "e5modd7                                              0.0   \n",
-       "e5xhbyd                                              3.0   \n",
-       "e5oaf7h                                              1.0   \n",
-       "e6nir3u                                              1.0   \n",
-       "e6c3xdn                                              0.0   \n",
-       "e5d3zaa                                              1.0   \n",
-       "e5gnjv9                                              0.0   \n",
-       "e69gw2t                                              2.0   \n",
-       "e5syrih                                              1.0   \n",
-       "e5sa2yf                                              1.0   \n",
-       "e6ai7z5                                              2.0   \n",
-       "...                                                  ...   \n",
-       "e5smhzk                                              1.0   \n",
-       "e5v91s0                                              0.0   \n",
-       "e6n6di6                                              1.0   \n",
-       "e6iqq30                                              0.0   \n",
-       "e5bfad7                                              0.0   \n",
-       "e6x5he5                                              0.0   \n",
-       "e6l9uyf                                              0.0   \n",
-       "e57hyr1                                              2.0   \n",
-       "e5b8sj7                                              1.0   \n",
-       "e6nlep7                                              0.0   \n",
-       "e6ltazd                                              1.0   \n",
-       "e57a6qq                                              2.0   \n",
-       "e5qc7eb                                              1.0   \n",
-       "e6hqt5y                                              0.0   \n",
-       "e5ua84v                                              3.0   \n",
-       "e65m7kq                                              1.0   \n",
-       "e5ggtru                                              0.0   \n",
-       "e5pmmig                                              3.0   \n",
-       "e64l6vq                                              1.0   \n",
-       "e6fjx0d                                              1.0   \n",
-       "e5h3xyy                                              1.0   \n",
-       "e589ri5                                              0.0   \n",
-       "e5beuqa                                              3.0   \n",
-       "e5lqoj1                                              1.0   \n",
-       "e5kvch1                                              2.0   \n",
-       "e6srvwm                                              1.0   \n",
-       "e5o65mk                                              1.0   \n",
-       "e647cm8                                              0.0   \n",
-       "e58n526                                              0.0   \n",
-       "e69r2kg                                              1.0   \n",
-       "\n",
-       "         count[dyadic interaction motif]  \\\n",
-       "e6p7yrp                              3.0   \n",
-       "e5ywqyk                              2.0   \n",
-       "e5qv9rj                              0.0   \n",
-       "e6jhojf                              4.0   \n",
-       "e6989ii                              1.0   \n",
-       "e69lgse                              1.0   \n",
-       "e5kwkg2                              0.0   \n",
-       "e6mehe7                              3.0   \n",
-       "e6m0hsd                              2.0   \n",
-       "e64r385                              2.0   \n",
-       "e5surbt                              0.0   \n",
-       "e58gxii                              3.0   \n",
-       "e64vc8y                              0.0   \n",
-       "e57504g                              1.0   \n",
-       "e5borjq                              2.0   \n",
-       "e64n9zv                              2.0   \n",
-       "e582ud3                              0.0   \n",
-       "e64i9cf                              2.0   \n",
-       "e6q9204                              2.0   \n",
-       "e5modd7                              0.0   \n",
-       "e5xhbyd                              3.0   \n",
-       "e5oaf7h                              1.0   \n",
-       "e6nir3u                              1.0   \n",
-       "e6c3xdn                              0.0   \n",
-       "e5d3zaa                              1.0   \n",
-       "e5gnjv9                              0.0   \n",
-       "e69gw2t                              3.0   \n",
-       "e5syrih                              2.0   \n",
-       "e5sa2yf                              1.0   \n",
-       "e6ai7z5                              2.0   \n",
-       "...                                  ...   \n",
-       "e5smhzk                              2.0   \n",
-       "e5v91s0                              0.0   \n",
-       "e6n6di6                              1.0   \n",
-       "e6iqq30                              1.0   \n",
-       "e5bfad7                              2.0   \n",
-       "e6x5he5                              4.0   \n",
-       "e6l9uyf                              0.0   \n",
-       "e57hyr1                              2.0   \n",
-       "e5b8sj7                              2.0   \n",
-       "e6nlep7                              0.0   \n",
-       "e6ltazd                              1.0   \n",
-       "e57a6qq                              2.0   \n",
-       "e5qc7eb                              1.0   \n",
-       "e6hqt5y                              0.0   \n",
-       "e5ua84v                              3.0   \n",
-       "e65m7kq                              1.0   \n",
-       "e5ggtru                              0.0   \n",
-       "e5pmmig                              3.0   \n",
-       "e64l6vq                              2.0   \n",
-       "e6fjx0d                              1.0   \n",
-       "e5h3xyy                              1.0   \n",
-       "e589ri5                              0.0   \n",
-       "e5beuqa                              3.0   \n",
-       "e5lqoj1                              1.0   \n",
-       "e5kvch1                              2.0   \n",
-       "e6srvwm                              1.0   \n",
-       "e5o65mk                              1.0   \n",
-       "e647cm8                              1.0   \n",
-       "e58n526                              0.0   \n",
-       "e69r2kg                              2.0   \n",
+       "         prop-nonzero[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                    1.000000   \n",
+       "e5ytz1d                                    0.444444   \n",
+       "e6ls80j                                    0.571429   \n",
+       "e5mhgl5                                    0.750000   \n",
+       "e6w6fah                                    0.111111   \n",
+       "...                                             ...   \n",
+       "e65ca8k                                    0.500000   \n",
+       "e6cdkpy                                    0.400000   \n",
+       "e5wc4tj                                    1.000000   \n",
+       "e6ua0sb                                    0.800000   \n",
+       "e5ua84v                                    0.714286   \n",
        "\n",
-       "         count[external reciprocity motif over mid-thread]  \\\n",
-       "e6p7yrp                                                2.0   \n",
-       "e5ywqyk                                                1.0   \n",
-       "e5qv9rj                                                5.0   \n",
-       "e6jhojf                                                4.0   \n",
-       "e6989ii                                                0.0   \n",
-       "e69lgse                                                2.0   \n",
-       "e5kwkg2                                                3.0   \n",
-       "e6mehe7                                                1.0   \n",
-       "e6m0hsd                                                0.0   \n",
-       "e64r385                                                2.0   \n",
-       "e5surbt                                                3.0   \n",
-       "e58gxii                                                3.0   \n",
-       "e64vc8y                                                1.0   \n",
-       "e57504g                                                4.0   \n",
-       "e5borjq                                                1.0   \n",
-       "e64n9zv                                                1.0   \n",
-       "e582ud3                                                0.0   \n",
-       "e64i9cf                                                0.0   \n",
-       "e6q9204                                                2.0   \n",
-       "e5modd7                                                6.0   \n",
-       "e5xhbyd                                                1.0   \n",
-       "e5oaf7h                                                1.0   \n",
-       "e6nir3u                                                0.0   \n",
-       "e6c3xdn                                                6.0   \n",
-       "e5d3zaa                                                2.0   \n",
-       "e5gnjv9                                                0.0   \n",
-       "e69gw2t                                                1.0   \n",
-       "e5syrih                                                4.0   \n",
-       "e5sa2yf                                                0.0   \n",
-       "e6ai7z5                                                1.0   \n",
-       "...                                                    ...   \n",
-       "e5smhzk                                                0.0   \n",
-       "e5v91s0                                                1.0   \n",
-       "e6n6di6                                                5.0   \n",
-       "e6iqq30                                                0.0   \n",
-       "e5bfad7                                                3.0   \n",
-       "e6x5he5                                                0.0   \n",
-       "e6l9uyf                                                1.0   \n",
-       "e57hyr1                                                1.0   \n",
-       "e5b8sj7                                                2.0   \n",
-       "e6nlep7                                                0.0   \n",
-       "e6ltazd                                                0.0   \n",
-       "e57a6qq                                                3.0   \n",
-       "e5qc7eb                                                4.0   \n",
-       "e6hqt5y                                                0.0   \n",
-       "e5ua84v                                                2.0   \n",
-       "e65m7kq                                                2.0   \n",
-       "e5ggtru                                                4.0   \n",
-       "e5pmmig                                                2.0   \n",
-       "e64l6vq                                                0.0   \n",
-       "e6fjx0d                                                0.0   \n",
-       "e5h3xyy                                                1.0   \n",
-       "e589ri5                                                1.0   \n",
-       "e5beuqa                                                1.0   \n",
-       "e5lqoj1                                                0.0   \n",
-       "e5kvch1                                                1.0   \n",
-       "e6srvwm                                                1.0   \n",
-       "e5o65mk                                                0.0   \n",
-       "e647cm8                                                1.0   \n",
-       "e58n526                                                0.0   \n",
-       "e69r2kg                                                4.0   \n",
+       "         prop-multiple[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                      0.600000   \n",
+       "e5ytz1d                                      0.000000   \n",
+       "e6ls80j                                      0.333333   \n",
+       "e5mhgl5                                      0.142857   \n",
+       "e6w6fah                                      0.000000   \n",
+       "...                                               ...   \n",
+       "e65ca8k                                      0.000000   \n",
+       "e6cdkpy                                      0.000000   \n",
+       "e5wc4tj                                      0.000000   \n",
+       "e6ua0sb                                      0.400000   \n",
+       "e5ua84v                                      0.333333   \n",
        "\n",
-       "         count[external reciprocity motif]  \\\n",
-       "e6p7yrp                                2.0   \n",
-       "e5ywqyk                                2.0   \n",
-       "e5qv9rj                                6.0   \n",
-       "e6jhojf                                4.0   \n",
-       "e6989ii                                0.0   \n",
-       "e69lgse                                4.0   \n",
-       "e5kwkg2                                6.0   \n",
-       "e6mehe7                                2.0   \n",
-       "e6m0hsd                                1.0   \n",
-       "e64r385                                5.0   \n",
-       "e5surbt                                4.0   \n",
-       "e58gxii                                3.0   \n",
-       "e64vc8y                                3.0   \n",
-       "e57504g                                6.0   \n",
-       "e5borjq                                5.0   \n",
-       "e64n9zv                                1.0   \n",
-       "e582ud3                                3.0   \n",
-       "e64i9cf                                1.0   \n",
-       "e6q9204                                4.0   \n",
-       "e5modd7                                8.0   \n",
-       "e5xhbyd                                2.0   \n",
-       "e5oaf7h                                2.0   \n",
-       "e6nir3u                                0.0   \n",
-       "e6c3xdn                                8.0   \n",
-       "e5d3zaa                                4.0   \n",
-       "e5gnjv9                                1.0   \n",
-       "e69gw2t                                2.0   \n",
-       "e5syrih                                6.0   \n",
-       "e5sa2yf                                0.0   \n",
-       "e6ai7z5                                4.0   \n",
-       "...                                    ...   \n",
-       "e5smhzk                                0.0   \n",
-       "e5v91s0                                4.0   \n",
-       "e6n6di6                                7.0   \n",
-       "e6iqq30                                2.0   \n",
-       "e5bfad7                                4.0   \n",
-       "e6x5he5                                0.0   \n",
-       "e6l9uyf                                4.0   \n",
-       "e57hyr1                                3.0   \n",
-       "e5b8sj7                                4.0   \n",
-       "e6nlep7                                0.0   \n",
-       "e6ltazd                                4.0   \n",
-       "e57a6qq                                3.0   \n",
-       "e5qc7eb                                4.0   \n",
-       "e6hqt5y                                5.0   \n",
-       "e5ua84v                                5.0   \n",
-       "e65m7kq                                4.0   \n",
-       "e5ggtru                                8.0   \n",
-       "e5pmmig                                4.0   \n",
-       "e64l6vq                                2.0   \n",
-       "e6fjx0d                                1.0   \n",
-       "e5h3xyy                                4.0   \n",
-       "e589ri5                                3.0   \n",
-       "e5beuqa                                4.0   \n",
-       "e5lqoj1                                2.0   \n",
-       "e5kvch1                                3.0   \n",
-       "e6srvwm                                5.0   \n",
-       "e5o65mk                                0.0   \n",
-       "e647cm8                                4.0   \n",
-       "e58n526                                0.0   \n",
-       "e69r2kg                                5.0   \n",
-       "\n",
-       "         count[incoming triads over mid-thread]  count[incoming triads]  \\\n",
-       "e6p7yrp                                     3.0                    10.0   \n",
-       "e5ywqyk                                     1.0                     2.0   \n",
-       "e5qv9rj                                     3.0                     6.0   \n",
-       "e6jhojf                                     3.0                     6.0   \n",
-       "e6989ii                                     0.0                     0.0   \n",
-       "e69lgse                                     3.0                     6.0   \n",
-       "e5kwkg2                                     1.0                     4.0   \n",
-       "e6mehe7                                     1.0                     7.0   \n",
-       "e6m0hsd                                     1.0                     1.0   \n",
-       "e64r385                                     2.0                     3.0   \n",
-       "e5surbt                                     0.0                    10.0   \n",
-       "e58gxii                                     4.0                     7.0   \n",
-       "e64vc8y                                     0.0                    15.0   \n",
-       "e57504g                                     2.0                     3.0   \n",
-       "e5borjq                                     4.0                     5.0   \n",
-       "e64n9zv                                     1.0                     1.0   \n",
-       "e582ud3                                     1.0                    16.0   \n",
-       "e64i9cf                                     1.0                     7.0   \n",
-       "e6q9204                                     4.0                     4.0   \n",
-       "e5modd7                                     8.0                     8.0   \n",
-       "e5xhbyd                                     2.0                     2.0   \n",
-       "e5oaf7h                                     3.0                     3.0   \n",
-       "e6nir3u                                     0.0                     0.0   \n",
-       "e6c3xdn                                     1.0                     1.0   \n",
-       "e5d3zaa                                     2.0                     3.0   \n",
-       "e5gnjv9                                     0.0                    28.0   \n",
-       "e69gw2t                                     2.0                     3.0   \n",
-       "e5syrih                                     8.0                     8.0   \n",
-       "e5sa2yf                                     0.0                     0.0   \n",
-       "e6ai7z5                                     1.0                     4.0   \n",
-       "...                                         ...                     ...   \n",
-       "e5smhzk                                     0.0                     1.0   \n",
-       "e5v91s0                                     1.0                    11.0   \n",
-       "e6n6di6                                     7.0                     7.0   \n",
-       "e6iqq30                                     0.0                    15.0   \n",
-       "e5bfad7                                     2.0                     8.0   \n",
-       "e6x5he5                                     0.0                     6.0   \n",
-       "e6l9uyf                                     1.0                    11.0   \n",
-       "e57hyr1                                     1.0                     7.0   \n",
-       "e5b8sj7                                     7.0                    10.0   \n",
-       "e6nlep7                                     0.0                    36.0   \n",
-       "e6ltazd                                     6.0                     6.0   \n",
-       "e57a6qq                                     4.0                     4.0   \n",
-       "e5qc7eb                                     4.0                     6.0   \n",
-       "e6hqt5y                                     6.0                    12.0   \n",
-       "e5ua84v                                     7.0                     7.0   \n",
-       "e65m7kq                                     3.0                     9.0   \n",
-       "e5ggtru                                    11.0                    11.0   \n",
-       "e5pmmig                                     2.0                     2.0   \n",
-       "e64l6vq                                     1.0                     4.0   \n",
-       "e6fjx0d                                     0.0                     1.0   \n",
-       "e5h3xyy                                     1.0                     7.0   \n",
-       "e589ri5                                     0.0                    15.0   \n",
-       "e5beuqa                                     6.0                     7.0   \n",
-       "e5lqoj1                                     0.0                    10.0   \n",
-       "e5kvch1                                     1.0                     4.0   \n",
-       "e6srvwm                                     2.0                     5.0   \n",
-       "e5o65mk                                     0.0                     0.0   \n",
-       "e647cm8                                     3.0                     9.0   \n",
-       "e58n526                                     0.0                    36.0   \n",
-       "e69r2kg                                     4.0                     5.0   \n",
-       "\n",
-       "         count[outgoing triads over mid-thread]  count[outgoing triads]  \\\n",
-       "e6p7yrp                                     3.0                     3.0   \n",
-       "e5ywqyk                                     1.0                     1.0   \n",
-       "e5qv9rj                                     0.0                     0.0   \n",
-       "e6jhojf                                     6.0                     6.0   \n",
-       "e6989ii                                     0.0                     0.0   \n",
-       "e69lgse                                     1.0                     1.0   \n",
-       "e5kwkg2                                     0.0                     0.0   \n",
-       "e6mehe7                                     3.0                     3.0   \n",
-       "e6m0hsd                                     1.0                     1.0   \n",
-       "e64r385                                     1.0                     2.0   \n",
-       "e5surbt                                     0.0                     0.0   \n",
-       "e58gxii                                     3.0                     3.0   \n",
-       "e64vc8y                                     0.0                     0.0   \n",
-       "e57504g                                     1.0                     2.0   \n",
-       "e5borjq                                     0.0                     1.0   \n",
-       "e64n9zv                                     1.0                     1.0   \n",
-       "e582ud3                                     0.0                     0.0   \n",
-       "e64i9cf                                     1.0                     1.0   \n",
-       "e6q9204                                     1.0                     3.0   \n",
-       "e5modd7                                     0.0                     0.0   \n",
-       "e5xhbyd                                     2.0                     2.0   \n",
-       "e5oaf7h                                     1.0                     1.0   \n",
-       "e6nir3u                                     0.0                     0.0   \n",
-       "e6c3xdn                                     0.0                     0.0   \n",
-       "e5d3zaa                                     0.0                     1.0   \n",
-       "e5gnjv9                                     0.0                     1.0   \n",
-       "e69gw2t                                     1.0                     2.0   \n",
-       "e5syrih                                     1.0                     2.0   \n",
-       "e5sa2yf                                     0.0                     0.0   \n",
-       "e6ai7z5                                     6.0                     6.0   \n",
-       "...                                         ...                     ...   \n",
-       "e5smhzk                                     1.0                     1.0   \n",
-       "e5v91s0                                     0.0                     0.0   \n",
-       "e6n6di6                                     1.0                     1.0   \n",
-       "e6iqq30                                     0.0                     0.0   \n",
-       "e5bfad7                                     1.0                     1.0   \n",
-       "e6x5he5                                     6.0                     6.0   \n",
-       "e6l9uyf                                     0.0                     1.0   \n",
-       "e57hyr1                                     0.0                     3.0   \n",
-       "e5b8sj7                                     0.0                     1.0   \n",
-       "e6nlep7                                     0.0                     0.0   \n",
-       "e6ltazd                                     0.0                     1.0   \n",
-       "e57a6qq                                     1.0                     1.0   \n",
-       "e5qc7eb                                     0.0                     1.0   \n",
-       "e6hqt5y                                     0.0                     1.0   \n",
-       "e5ua84v                                     2.0                     4.0   \n",
-       "e65m7kq                                     0.0                     1.0   \n",
-       "e5ggtru                                     0.0                     1.0   \n",
-       "e5pmmig                                     2.0                     4.0   \n",
-       "e64l6vq                                     1.0                     1.0   \n",
-       "e6fjx0d                                     0.0                     1.0   \n",
-       "e5h3xyy                                     0.0                     1.0   \n",
-       "e589ri5                                     0.0                     0.0   \n",
-       "e5beuqa                                     3.0                     7.0   \n",
-       "e5lqoj1                                     1.0                     3.0   \n",
-       "e5kvch1                                     0.0                     2.0   \n",
-       "e6srvwm                                     0.0                     1.0   \n",
-       "e5o65mk                                     0.0                     0.0   \n",
-       "e647cm8                                     0.0                     0.0   \n",
-       "e58n526                                     0.0                     0.0   \n",
-       "e69r2kg                                     1.0                     1.0   \n",
-       "\n",
-       "         count[reciprocity motif over mid-thread]  count[reciprocity motif]  \\\n",
-       "e6p7yrp                                       2.0                       4.0   \n",
-       "e5ywqyk                                       5.0                       6.0   \n",
-       "e5qv9rj                                       0.0                       0.0   \n",
-       "e6jhojf                                       3.0                       4.0   \n",
-       "e6989ii                                       7.0                       8.0   \n",
-       "e69lgse                                       1.0                       2.0   \n",
-       "e5kwkg2                                       0.0                       0.0   \n",
-       "e6mehe7                                       2.0                       4.0   \n",
-       "e6m0hsd                                       6.0                       7.0   \n",
-       "e64r385                                       2.0                       2.0   \n",
-       "e5surbt                                       0.0                       0.0   \n",
-       "e58gxii                                       2.0                       4.0   \n",
-       "e64vc8y                                       0.0                       0.0   \n",
-       "e57504g                                       1.0                       1.0   \n",
-       "e5borjq                                       1.0                       2.0   \n",
-       "e64n9zv                                       6.0                       7.0   \n",
-       "e582ud3                                       0.0                       0.0   \n",
-       "e64i9cf                                       2.0                       4.0   \n",
-       "e6q9204                                       4.0                       4.0   \n",
-       "e5modd7                                       0.0                       0.0   \n",
-       "e5xhbyd                                       5.0                       6.0   \n",
-       "e5oaf7h                                       5.0                       6.0   \n",
-       "e6nir3u                                       7.0                       8.0   \n",
-       "e6c3xdn                                       0.0                       0.0   \n",
-       "e5d3zaa                                       3.0                       3.0   \n",
-       "e5gnjv9                                       0.0                       0.0   \n",
-       "e69gw2t                                       4.0                       5.0   \n",
-       "e5syrih                                       1.0                       2.0   \n",
-       "e5sa2yf                                       7.0                       8.0   \n",
-       "e6ai7z5                                       2.0                       2.0   \n",
-       "...                                           ...                       ...   \n",
-       "e5smhzk                                       5.0                       7.0   \n",
-       "e5v91s0                                       0.0                       0.0   \n",
-       "e6n6di6                                       1.0                       1.0   \n",
-       "e6iqq30                                       0.0                       1.0   \n",
-       "e5bfad7                                       0.0                       2.0   \n",
-       "e6x5he5                                       0.0                       5.0   \n",
-       "e6l9uyf                                       0.0                       0.0   \n",
-       "e57hyr1                                       2.0                       2.0   \n",
-       "e5b8sj7                                       1.0                       2.0   \n",
-       "e6nlep7                                       0.0                       0.0   \n",
-       "e6ltazd                                       4.0                       4.0   \n",
-       "e57a6qq                                       4.0                       5.0   \n",
-       "e5qc7eb                                       2.0                       3.0   \n",
-       "e6hqt5y                                       0.0                       0.0   \n",
-       "e5ua84v                                       3.0                       3.0   \n",
-       "e65m7kq                                       1.0                       1.0   \n",
-       "e5ggtru                                       0.0                       0.0   \n",
-       "e5pmmig                                       4.0                       4.0   \n",
-       "e64l6vq                                       2.0                       4.0   \n",
-       "e6fjx0d                                       6.0                       6.0   \n",
-       "e5h3xyy                                       1.0                       1.0   \n",
-       "e589ri5                                       0.0                       0.0   \n",
-       "e5beuqa                                       3.0                       3.0   \n",
-       "e5lqoj1                                       2.0                       2.0   \n",
-       "e5kvch1                                       3.0                       3.0   \n",
-       "e6srvwm                                       1.0                       1.0   \n",
-       "e5o65mk                                       5.0                       7.0   \n",
-       "e647cm8                                       0.0                       1.0   \n",
-       "e58n526                                       0.0                       0.0   \n",
-       "e69r2kg                                       1.0                       2.0   \n",
+       "         prop-multiple[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                     0.400000   \n",
+       "e5ytz1d                                     0.750000   \n",
+       "e6ls80j                                     0.500000   \n",
+       "e5mhgl5                                     0.333333   \n",
+       "e6w6fah                                     1.000000   \n",
+       "...                                              ...   \n",
+       "e65ca8k                                     1.000000   \n",
+       "e6cdkpy                                     0.750000   \n",
+       "e5wc4tj                                     0.000000   \n",
+       "e6ua0sb                                     0.250000   \n",
+       "e5ua84v                                     0.400000   \n",
        "\n",
-       "         entropy[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                          1.242453   \n",
-       "e5ywqyk                                          1.039721   \n",
-       "e5qv9rj                                          1.242453   \n",
-       "e6jhojf                                          1.475076   \n",
-       "e6989ii                                          0.693147   \n",
-       "e69lgse                                          1.242453   \n",
-       "e5kwkg2                                          1.560710   \n",
-       "e6mehe7                                          1.332179   \n",
-       "e6m0hsd                                          1.039721   \n",
-       "e64r385                                          1.549826   \n",
-       "e5surbt                                          1.386294   \n",
-       "e58gxii                                          1.277034   \n",
-       "e64vc8y                                          1.098612   \n",
-       "e57504g                                          1.549826   \n",
-       "e5borjq                                          1.277034   \n",
-       "e64n9zv                                          1.039721   \n",
-       "e582ud3                                          0.636514   \n",
-       "e64i9cf                                          1.039721   \n",
-       "e6q9204                                          1.011404   \n",
-       "e5modd7                                          1.039721   \n",
-       "e5xhbyd                                          1.329661   \n",
-       "e5oaf7h                                          0.562335   \n",
-       "e6nir3u                                          0.693147   \n",
-       "e6c3xdn                                          1.906155   \n",
-       "e5d3zaa                                          1.054920   \n",
-       "e5gnjv9                                          0.000000   \n",
-       "e69gw2t                                          1.054920   \n",
-       "e5syrih                                          1.039721   \n",
-       "e5sa2yf                                          0.693147   \n",
-       "e6ai7z5                                          1.560710   \n",
-       "...                                                   ...   \n",
-       "e5smhzk                                          1.098612   \n",
-       "e5v91s0                                          1.039721   \n",
-       "e6n6di6                                          1.213008   \n",
-       "e6iqq30                                          1.098612   \n",
-       "e5bfad7                                          1.329661   \n",
-       "e6x5he5                                          1.386294   \n",
-       "e6l9uyf                                          1.039721   \n",
-       "e57hyr1                                          1.332179   \n",
-       "e5b8sj7                                          0.636514   \n",
-       "e6nlep7                                               NaN   \n",
-       "e6ltazd                                          0.500402   \n",
-       "e57a6qq                                          1.011404   \n",
-       "e5qc7eb                                          1.011404   \n",
-       "e6hqt5y                                          0.500402   \n",
-       "e5ua84v                                          1.213008   \n",
-       "e65m7kq                                          0.950271   \n",
-       "e5ggtru                                          0.900256   \n",
-       "e5pmmig                                          1.329661   \n",
-       "e64l6vq                                          1.332179   \n",
-       "e6fjx0d                                          0.693147   \n",
-       "e5h3xyy                                          1.332179   \n",
-       "e589ri5                                          1.098612   \n",
-       "e5beuqa                                          1.153742   \n",
-       "e5lqoj1                                          1.098612   \n",
-       "e5kvch1                                          1.332179   \n",
-       "e6srvwm                                          1.329661   \n",
-       "e5o65mk                                          0.693147   \n",
-       "e647cm8                                          0.950271   \n",
-       "e58n526                                               NaN   \n",
-       "e69r2kg                                          1.277034   \n",
+       "         entropy[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                1.559581   \n",
+       "e5ytz1d                                2.197225   \n",
+       "e6ls80j                                1.676988   \n",
+       "e5mhgl5                                1.906155   \n",
+       "e6w6fah                                2.079442   \n",
+       "...                                         ...   \n",
+       "e65ca8k                                0.693147   \n",
+       "e6cdkpy                                2.197225   \n",
+       "e5wc4tj                                0.693147   \n",
+       "e6ua0sb                                1.549826   \n",
+       "e5ua84v                                1.676988   \n",
        "\n",
        "         entropy[indegree over C->C responses]  \\\n",
-       "e6p7yrp                               1.073543   \n",
-       "e5ywqyk                               1.054920   \n",
-       "e5qv9rj                               1.464816   \n",
-       "e6jhojf                               1.386294   \n",
-       "e6989ii                               0.693147   \n",
-       "e69lgse                               1.255482   \n",
-       "e5kwkg2                               1.676988   \n",
-       "e6mehe7                               1.213008   \n",
-       "e6m0hsd                               1.039721   \n",
-       "e64r385                               1.735126   \n",
-       "e5surbt                               1.303092   \n",
-       "e58gxii                               1.213008   \n",
-       "e64vc8y                               1.002718   \n",
-       "e57504g                               1.735126   \n",
-       "e5borjq                               1.522955   \n",
-       "e64n9zv                               1.039721   \n",
-       "e582ud3                               0.848686   \n",
-       "e64i9cf                               0.955700   \n",
-       "e6q9204                               1.277034   \n",
-       "e5modd7                               1.273028   \n",
-       "e5xhbyd                               1.329661   \n",
-       "e5oaf7h                               0.562335   \n",
-       "e6nir3u                               0.693147   \n",
-       "e6c3xdn                               2.043192   \n",
-       "e5d3zaa                               1.351784   \n",
-       "e5gnjv9                               0.348832   \n",
-       "e69gw2t                               1.351784   \n",
-       "e5syrih                               1.273028   \n",
-       "e5sa2yf                               0.693147   \n",
-       "e6ai7z5                               1.494175   \n",
+       "e5hm9mp                               1.494175   \n",
+       "e5ytz1d                               1.310784   \n",
+       "e6ls80j                               1.214890   \n",
+       "e5mhgl5                               1.732868   \n",
+       "e6w6fah                               0.000000   \n",
        "...                                        ...   \n",
-       "e5smhzk                               1.039721   \n",
-       "e5v91s0                               1.149060   \n",
-       "e6n6di6                               1.427061   \n",
-       "e6iqq30                               1.002718   \n",
-       "e5bfad7                               1.273028   \n",
-       "e6x5he5                               1.386294   \n",
-       "e6l9uyf                               1.149060   \n",
-       "e57hyr1                               1.427061   \n",
-       "e5b8sj7                               1.060857   \n",
-       "e6nlep7                               0.000000   \n",
-       "e6ltazd                               0.867563   \n",
-       "e57a6qq                               1.011404   \n",
-       "e5qc7eb                               1.004242   \n",
-       "e6hqt5y                               0.964963   \n",
+       "e65ca8k                               0.000000   \n",
+       "e6cdkpy                               1.273028   \n",
+       "e5wc4tj                               0.693147   \n",
+       "e6ua0sb                               1.153742   \n",
        "e5ua84v                               1.427061   \n",
-       "e65m7kq                               1.214890   \n",
-       "e5ggtru                               1.149060   \n",
-       "e5pmmig                               1.549826   \n",
-       "e64l6vq                               1.277034   \n",
-       "e6fjx0d                               1.039721   \n",
-       "e5h3xyy                               1.427061   \n",
-       "e589ri5                               1.002718   \n",
-       "e5beuqa                               1.427061   \n",
-       "e5lqoj1                               1.073543   \n",
-       "e5kvch1                               1.494175   \n",
-       "e6srvwm                               1.522955   \n",
-       "e5o65mk                               0.693147   \n",
-       "e647cm8                               1.214890   \n",
-       "e58n526                               0.000000   \n",
-       "e69r2kg                               1.522955   \n",
-       "\n",
-       "         entropy[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                          1.791759   \n",
-       "e5ywqyk                                          1.906155   \n",
-       "e5qv9rj                                          1.242453   \n",
-       "e6jhojf                                          1.906155   \n",
-       "e6989ii                                          1.945910   \n",
-       "e69lgse                                          1.242453   \n",
-       "e5kwkg2                                          1.560710   \n",
-       "e6mehe7                                          1.560710   \n",
-       "e6m0hsd                                          1.906155   \n",
-       "e64r385                                          1.549826   \n",
-       "e5surbt                                          1.386294   \n",
-       "e58gxii                                          1.549826   \n",
-       "e64vc8y                                          1.098612   \n",
-       "e57504g                                          1.549826   \n",
-       "e5borjq                                          1.277034   \n",
-       "e64n9zv                                          1.906155   \n",
-       "e582ud3                                          0.636514   \n",
-       "e64i9cf                                          1.332179   \n",
-       "e6q9204                                          1.732868   \n",
-       "e5modd7                                          1.039721   \n",
-       "e5xhbyd                                          1.732868   \n",
-       "e5oaf7h                                          1.732868   \n",
-       "e6nir3u                                          1.945910   \n",
-       "e6c3xdn                                          1.906155   \n",
-       "e5d3zaa                                          1.549826   \n",
-       "e5gnjv9                                          0.000000   \n",
-       "e69gw2t                                          1.549826   \n",
-       "e5syrih                                          1.494175   \n",
-       "e5sa2yf                                          2.079442   \n",
-       "e6ai7z5                                          1.791759   \n",
-       "...                                                   ...   \n",
-       "e5smhzk                                          1.945910   \n",
-       "e5v91s0                                          1.039721   \n",
-       "e6n6di6                                          1.494175   \n",
-       "e6iqq30                                          1.098612   \n",
-       "e5bfad7                                          1.329661   \n",
-       "e6x5he5                                          1.386294   \n",
-       "e6l9uyf                                          1.039721   \n",
-       "e57hyr1                                          1.332179   \n",
-       "e5b8sj7                                          1.011404   \n",
-       "e6nlep7                                               NaN   \n",
-       "e6ltazd                                          1.386294   \n",
-       "e57a6qq                                          1.732868   \n",
-       "e5qc7eb                                          1.277034   \n",
-       "e6hqt5y                                          0.500402   \n",
-       "e5ua84v                                          1.494175   \n",
-       "e65m7kq                                          1.332179   \n",
-       "e5ggtru                                          1.213008   \n",
-       "e5pmmig                                          1.906155   \n",
-       "e64l6vq                                          1.560710   \n",
-       "e6fjx0d                                          1.945910   \n",
-       "e5h3xyy                                          1.332179   \n",
-       "e589ri5                                          1.098612   \n",
-       "e5beuqa                                          1.475076   \n",
-       "e5lqoj1                                          1.386294   \n",
-       "e5kvch1                                          1.791759   \n",
-       "e6srvwm                                          1.329661   \n",
-       "e5o65mk                                          1.945910   \n",
-       "e647cm8                                          0.950271   \n",
-       "e58n526                                               NaN   \n",
-       "e69r2kg                                          1.549826   \n",
-       "\n",
-       "         entropy[indegree over C->c responses]  \\\n",
-       "e6p7yrp                               1.831020   \n",
-       "e5ywqyk                               2.043192   \n",
-       "e5qv9rj                               1.464816   \n",
-       "e6jhojf                               2.043192   \n",
-       "e6989ii                               2.079442   \n",
-       "e69lgse                               1.464816   \n",
-       "e5kwkg2                               1.676988   \n",
-       "e6mehe7                               1.676988   \n",
-       "e6m0hsd                               2.043192   \n",
-       "e64r385                               1.735126   \n",
-       "e5surbt                               1.303092   \n",
-       "e58gxii                               1.735126   \n",
-       "e64vc8y                               1.002718   \n",
-       "e57504g                               1.735126   \n",
-       "e5borjq                               1.522955   \n",
-       "e64n9zv                               2.043192   \n",
-       "e582ud3                               0.848686   \n",
-       "e64i9cf                               1.427061   \n",
-       "e6q9204                               1.889159   \n",
-       "e5modd7                               1.273028   \n",
-       "e5xhbyd                               1.889159   \n",
-       "e5oaf7h                               1.889159   \n",
-       "e6nir3u                               2.079442   \n",
-       "e6c3xdn                               2.043192   \n",
-       "e5d3zaa                               1.735126   \n",
-       "e5gnjv9                               0.348832   \n",
-       "e69gw2t                               1.735126   \n",
-       "e5syrih                               1.676988   \n",
-       "e5sa2yf                               2.197225   \n",
-       "e6ai7z5                               1.831020   \n",
-       "...                                        ...   \n",
-       "e5smhzk                               2.043192   \n",
-       "e5v91s0                               1.149060   \n",
-       "e6n6di6                               1.676988   \n",
-       "e6iqq30                               1.002718   \n",
-       "e5bfad7                               1.522955   \n",
-       "e6x5he5                               1.386294   \n",
-       "e6l9uyf                               1.149060   \n",
-       "e57hyr1                               1.427061   \n",
-       "e5b8sj7                               1.310784   \n",
-       "e6nlep7                               0.000000   \n",
-       "e6ltazd                               1.581094   \n",
-       "e57a6qq                               1.889159   \n",
-       "e5qc7eb                               1.522955   \n",
-       "e6hqt5y                               0.964963   \n",
-       "e5ua84v                               1.676988   \n",
-       "e65m7kq                               1.427061   \n",
-       "e5ggtru                               1.427061   \n",
-       "e5pmmig                               2.043192   \n",
-       "e64l6vq                               1.676988   \n",
-       "e6fjx0d                               2.043192   \n",
-       "e5h3xyy                               1.427061   \n",
-       "e589ri5                               1.002718   \n",
-       "e5beuqa                               1.676988   \n",
-       "e5lqoj1                               1.303092   \n",
-       "e5kvch1                               1.831020   \n",
-       "e6srvwm                               1.522955   \n",
-       "e5o65mk                               2.079442   \n",
-       "e647cm8                               1.214890   \n",
-       "e58n526                               0.000000   \n",
-       "e69r2kg                               1.735126   \n",
        "\n",
-       "         entropy[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                          1.791759   \n",
-       "e5ywqyk                                          1.906155   \n",
-       "e5qv9rj                                          1.242453   \n",
-       "e6jhojf                                          1.906155   \n",
-       "e6989ii                                          1.906155   \n",
-       "e69lgse                                          1.242453   \n",
-       "e5kwkg2                                          1.560710   \n",
-       "e6mehe7                                          1.560710   \n",
-       "e6m0hsd                                          1.906155   \n",
-       "e64r385                                          1.549826   \n",
-       "e5surbt                                          1.386294   \n",
-       "e58gxii                                          1.549826   \n",
-       "e64vc8y                                          1.098612   \n",
-       "e57504g                                          1.549826   \n",
-       "e5borjq                                          1.277034   \n",
-       "e64n9zv                                          1.906155   \n",
-       "e582ud3                                          0.636514   \n",
-       "e64i9cf                                          1.332179   \n",
-       "e6q9204                                          1.732868   \n",
-       "e5modd7                                          1.039721   \n",
-       "e5xhbyd                                          1.732868   \n",
-       "e5oaf7h                                          1.732868   \n",
-       "e6nir3u                                          1.906155   \n",
-       "e6c3xdn                                          1.906155   \n",
-       "e5d3zaa                                          1.549826   \n",
-       "e5gnjv9                                          0.000000   \n",
-       "e69gw2t                                          1.549826   \n",
-       "e5syrih                                          1.494175   \n",
-       "e5sa2yf                                          2.079442   \n",
-       "e6ai7z5                                          1.791759   \n",
+       "         2nd-largest / max[outdegree over C->C responses]  \\\n",
+       "e5hm9mp                                          1.000000   \n",
+       "e5ytz1d                                          1.000000   \n",
+       "e6ls80j                                          0.666667   \n",
+       "e5mhgl5                                          0.500000   \n",
+       "e6w6fah                                          1.000000   \n",
        "...                                                   ...   \n",
-       "e5smhzk                                          1.945910   \n",
-       "e5v91s0                                          1.039721   \n",
-       "e6n6di6                                          1.494175   \n",
-       "e6iqq30                                          1.098612   \n",
-       "e5bfad7                                          1.329661   \n",
-       "e6x5he5                                          1.332179   \n",
-       "e6l9uyf                                          1.039721   \n",
-       "e57hyr1                                          1.332179   \n",
-       "e5b8sj7                                          1.011404   \n",
-       "e6nlep7                                               NaN   \n",
-       "e6ltazd                                          1.386294   \n",
-       "e57a6qq                                          1.732868   \n",
-       "e5qc7eb                                          1.277034   \n",
-       "e6hqt5y                                          0.500402   \n",
-       "e5ua84v                                          1.494175   \n",
-       "e65m7kq                                          1.332179   \n",
-       "e5ggtru                                          1.213008   \n",
-       "e5pmmig                                          1.906155   \n",
-       "e64l6vq                                          1.560710   \n",
-       "e6fjx0d                                          1.945910   \n",
-       "e5h3xyy                                          1.332179   \n",
-       "e589ri5                                          1.098612   \n",
-       "e5beuqa                                          1.475076   \n",
-       "e5lqoj1                                          1.386294   \n",
-       "e5kvch1                                          1.791759   \n",
-       "e6srvwm                                          1.329661   \n",
-       "e5o65mk                                          1.945910   \n",
-       "e647cm8                                          0.950271   \n",
-       "e58n526                                               NaN   \n",
-       "e69r2kg                                          1.549826   \n",
-       "\n",
-       "         entropy[indegree over c->c responses]  \\\n",
-       "e6p7yrp                               1.831020   \n",
-       "e5ywqyk                               2.043192   \n",
-       "e5qv9rj                               1.464816   \n",
-       "e6jhojf                               2.043192   \n",
-       "e6989ii                               2.043192   \n",
-       "e69lgse                               1.464816   \n",
-       "e5kwkg2                               1.676988   \n",
-       "e6mehe7                               1.676988   \n",
-       "e6m0hsd                               2.043192   \n",
-       "e64r385                               1.735126   \n",
-       "e5surbt                               1.303092   \n",
-       "e58gxii                               1.735126   \n",
-       "e64vc8y                               1.002718   \n",
-       "e57504g                               1.735126   \n",
-       "e5borjq                               1.522955   \n",
-       "e64n9zv                               2.043192   \n",
-       "e582ud3                               0.848686   \n",
-       "e64i9cf                               1.427061   \n",
-       "e6q9204                               1.889159   \n",
-       "e5modd7                               1.273028   \n",
-       "e5xhbyd                               1.889159   \n",
-       "e5oaf7h                               1.889159   \n",
-       "e6nir3u                               2.043192   \n",
-       "e6c3xdn                               2.043192   \n",
-       "e5d3zaa                               1.735126   \n",
-       "e5gnjv9                               0.348832   \n",
-       "e69gw2t                               1.735126   \n",
-       "e5syrih                               1.676988   \n",
-       "e5sa2yf                               2.197225   \n",
-       "e6ai7z5                               1.831020   \n",
-       "...                                        ...   \n",
-       "e5smhzk                               2.043192   \n",
-       "e5v91s0                               1.149060   \n",
-       "e6n6di6                               1.676988   \n",
-       "e6iqq30                               1.002718   \n",
-       "e5bfad7                               1.522955   \n",
-       "e6x5he5                               1.427061   \n",
-       "e6l9uyf                               1.149060   \n",
-       "e57hyr1                               1.427061   \n",
-       "e5b8sj7                               1.310784   \n",
-       "e6nlep7                               0.000000   \n",
-       "e6ltazd                               1.581094   \n",
-       "e57a6qq                               1.889159   \n",
-       "e5qc7eb                               1.522955   \n",
-       "e6hqt5y                               0.964963   \n",
-       "e5ua84v                               1.676988   \n",
-       "e65m7kq                               1.427061   \n",
-       "e5ggtru                               1.427061   \n",
-       "e5pmmig                               2.043192   \n",
-       "e64l6vq                               1.676988   \n",
-       "e6fjx0d                               2.043192   \n",
-       "e5h3xyy                               1.427061   \n",
-       "e589ri5                               1.002718   \n",
-       "e5beuqa                               1.676988   \n",
-       "e5lqoj1                               1.303092   \n",
-       "e5kvch1                               1.831020   \n",
-       "e6srvwm                               1.522955   \n",
-       "e5o65mk                               2.043192   \n",
-       "e647cm8                               1.214890   \n",
-       "e58n526                               0.000000   \n",
-       "e69r2kg                               1.735126   \n",
-       "\n",
-       "         entropy[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.242453   \n",
-       "e5ywqyk                                           1.039721   \n",
-       "e5qv9rj                                           1.791759   \n",
-       "e6jhojf                                           1.153742   \n",
-       "e6989ii                                           0.693147   \n",
-       "e69lgse                                           1.560710   \n",
-       "e5kwkg2                                           1.791759   \n",
-       "e6mehe7                                           0.950271   \n",
-       "e6m0hsd                                           1.039721   \n",
-       "e64r385                                           1.747868   \n",
-       "e5surbt                                           1.386294   \n",
-       "e58gxii                                           1.475076   \n",
-       "e64vc8y                                           1.098612   \n",
-       "e57504g                                           1.747868   \n",
-       "e5borjq                                           1.945910   \n",
-       "e64n9zv                                           1.039721   \n",
-       "e582ud3                                           1.098612   \n",
-       "e64i9cf                                           1.039721   \n",
-       "e6q9204                                           1.560710   \n",
-       "e5modd7                                           2.079442   \n",
-       "e5xhbyd                                           1.329661   \n",
-       "e5oaf7h                                           1.039721   \n",
-       "e6nir3u                                           0.693147   \n",
-       "e6c3xdn                                           2.079442   \n",
-       "e5d3zaa                                           1.609438   \n",
-       "e5gnjv9                                           0.000000   \n",
-       "e69gw2t                                           1.332179   \n",
-       "e5syrih                                           1.906155   \n",
-       "e5sa2yf                                           0.693147   \n",
-       "e6ai7z5                                           0.867563   \n",
-       "...                                                    ...   \n",
-       "e5smhzk                                           0.636514   \n",
-       "e5v91s0                                           1.386294   \n",
-       "e6n6di6                                           1.906155   \n",
-       "e6iqq30                                           1.098612   \n",
-       "e5bfad7                                           1.560710   \n",
-       "e6x5he5                                           0.000000   \n",
-       "e6l9uyf                                           1.386294   \n",
-       "e57hyr1                                           1.609438   \n",
-       "e5b8sj7                                           1.791759   \n",
-       "e6nlep7                                                NaN   \n",
-       "e6ltazd                                           1.609438   \n",
-       "e57a6qq                                           1.560710   \n",
-       "e5qc7eb                                           1.791759   \n",
-       "e6hqt5y                                           1.609438   \n",
-       "e5ua84v                                           1.732868   \n",
-       "e65m7kq                                           1.609438   \n",
-       "e5ggtru                                           2.079442   \n",
-       "e5pmmig                                           1.329661   \n",
-       "e64l6vq                                           1.332179   \n",
-       "e6fjx0d                                           0.693147   \n",
-       "e5h3xyy                                           1.609438   \n",
-       "e589ri5                                           1.098612   \n",
-       "e5beuqa                                           1.475076   \n",
-       "e5lqoj1                                           0.636514   \n",
-       "e5kvch1                                           1.609438   \n",
-       "e6srvwm                                           1.791759   \n",
-       "e5o65mk                                           0.693147   \n",
-       "e647cm8                                           1.609438   \n",
-       "e58n526                                                NaN   \n",
-       "e69r2kg                                           1.747868   \n",
+       "e65ca8k                                          1.000000   \n",
+       "e6cdkpy                                          1.000000   \n",
+       "e5wc4tj                                          1.000000   \n",
+       "e6ua0sb                                          1.000000   \n",
+       "e5ua84v                                          0.666667   \n",
        "\n",
-       "         entropy[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                1.667462   \n",
-       "e5ywqyk                                1.332179   \n",
-       "e5qv9rj                                2.197225   \n",
-       "e6jhojf                                1.386294   \n",
-       "e6989ii                                0.693147   \n",
-       "e69lgse                                1.906155   \n",
-       "e5kwkg2                                2.197225   \n",
-       "e6mehe7                                1.667462   \n",
-       "e6m0hsd                                1.039721   \n",
-       "e64r385                                1.889159   \n",
-       "e5surbt                                2.197225   \n",
-       "e58gxii                                1.667462   \n",
-       "e64vc8y                                2.197225   \n",
-       "e57504g                                1.889159   \n",
-       "e5borjq                                2.043192   \n",
-       "e64n9zv                                1.039721   \n",
-       "e582ud3                                2.197225   \n",
-       "e64i9cf                                1.747868   \n",
-       "e6q9204                                1.475076   \n",
-       "e5modd7                                2.197225   \n",
-       "e5xhbyd                                1.329661   \n",
-       "e5oaf7h                                1.039721   \n",
-       "e6nir3u                                0.693147   \n",
-       "e6c3xdn                                2.197225   \n",
-       "e5d3zaa                                1.747868   \n",
-       "e5gnjv9                                2.043192   \n",
-       "e69gw2t                                1.549826   \n",
-       "e5syrih                                1.889159   \n",
-       "e5sa2yf                                0.693147   \n",
-       "e6ai7z5                                1.386294   \n",
-       "...                                         ...   \n",
-       "e5smhzk                                1.039721   \n",
-       "e5v91s0                                2.197225   \n",
-       "e6n6di6                                2.043192   \n",
-       "e6iqq30                                2.197225   \n",
-       "e5bfad7                                2.043192   \n",
-       "e6x5he5                                1.386294   \n",
-       "e6l9uyf                                2.043192   \n",
-       "e57hyr1                                1.735126   \n",
-       "e5b8sj7                                2.043192   \n",
-       "e6nlep7                                2.197225   \n",
-       "e6ltazd                                1.560710   \n",
-       "e57a6qq                                1.560710   \n",
-       "e5qc7eb                                1.747868   \n",
-       "e6hqt5y                                2.043192   \n",
-       "e5ua84v                                1.676988   \n",
-       "e65m7kq                                2.043192   \n",
-       "e5ggtru                                2.043192   \n",
-       "e5pmmig                                1.277034   \n",
-       "e64l6vq                                1.747868   \n",
-       "e6fjx0d                                1.039721   \n",
-       "e5h3xyy                                2.043192   \n",
-       "e589ri5                                2.197225   \n",
-       "e5beuqa                                1.427061   \n",
-       "e5lqoj1                                1.667462   \n",
-       "e5kvch1                                1.732868   \n",
-       "e6srvwm                                2.043192   \n",
-       "e5o65mk                                0.693147   \n",
-       "e647cm8                                2.197225   \n",
-       "e58n526                                2.197225   \n",
-       "e69r2kg                                2.043192   \n",
+       "         2nd-largest / max[indegree over C->C responses]  \\\n",
+       "e5hm9mp                                         0.666667   \n",
+       "e5ytz1d                                         1.000000   \n",
+       "e6ls80j                                         0.750000   \n",
+       "e5mhgl5                                         1.000000   \n",
+       "e6w6fah                                         0.000000   \n",
+       "...                                                  ...   \n",
+       "e65ca8k                                         0.000000   \n",
+       "e6cdkpy                                         0.500000   \n",
+       "e5wc4tj                                         1.000000   \n",
+       "e6ua0sb                                         0.250000   \n",
+       "e5ua84v                                         0.500000   \n",
        "\n",
-       "         entropy[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.242453   \n",
-       "e5ywqyk                                           0.974315   \n",
-       "e5qv9rj                                           1.791759   \n",
-       "e6jhojf                                           1.213008   \n",
-       "e6989ii                                           0.682908   \n",
-       "e69lgse                                           1.560710   \n",
-       "e5kwkg2                                           1.791759   \n",
-       "e6mehe7                                           1.011404   \n",
-       "e6m0hsd                                           0.974315   \n",
-       "e64r385                                           1.747868   \n",
-       "e5surbt                                           1.386294   \n",
-       "e58gxii                                           1.475076   \n",
-       "e64vc8y                                           1.098612   \n",
-       "e57504g                                           1.747868   \n",
-       "e5borjq                                           1.945910   \n",
-       "e64n9zv                                           1.082196   \n",
-       "e582ud3                                           1.098612   \n",
-       "e64i9cf                                           0.950271   \n",
-       "e6q9204                                           1.494175   \n",
-       "e5modd7                                           2.079442   \n",
-       "e5xhbyd                                           1.320888   \n",
-       "e5oaf7h                                           0.974315   \n",
-       "e6nir3u                                           0.682908   \n",
-       "e6c3xdn                                           2.079442   \n",
-       "e5d3zaa                                           1.549826   \n",
-       "e5gnjv9                                           0.000000   \n",
-       "e69gw2t                                           1.277034   \n",
-       "e5syrih                                           1.906155   \n",
-       "e5sa2yf                                           0.693147   \n",
-       "e6ai7z5                                           0.867563   \n",
-       "...                                                    ...   \n",
-       "e5smhzk                                           0.682908   \n",
-       "e5v91s0                                           1.386294   \n",
-       "e6n6di6                                           1.906155   \n",
-       "e6iqq30                                           1.098612   \n",
-       "e5bfad7                                           1.560710   \n",
-       "e6x5he5                                           0.000000   \n",
-       "e6l9uyf                                           1.386294   \n",
-       "e57hyr1                                           1.609438   \n",
-       "e5b8sj7                                           1.791759   \n",
-       "e6nlep7                                                NaN   \n",
-       "e6ltazd                                           1.494175   \n",
-       "e57a6qq                                           1.494175   \n",
-       "e5qc7eb                                           1.747868   \n",
-       "e6hqt5y                                           1.609438   \n",
-       "e5ua84v                                           1.732868   \n",
-       "e65m7kq                                           1.609438   \n",
-       "e5ggtru                                           2.079442   \n",
-       "e5pmmig                                           1.320888   \n",
-       "e64l6vq                                           1.242453   \n",
-       "e6fjx0d                                           0.682908   \n",
-       "e5h3xyy                                           1.609438   \n",
-       "e589ri5                                           1.098612   \n",
-       "e5beuqa                                           1.475076   \n",
-       "e5lqoj1                                           0.693147   \n",
-       "e5kvch1                                           1.560710   \n",
-       "e6srvwm                                           1.791759   \n",
-       "e5o65mk                                           0.682908   \n",
-       "e647cm8                                           1.609438   \n",
-       "e58n526                                                NaN   \n",
-       "e69r2kg                                           1.747868   \n",
+       "         is-present[reciprocity motif]  count[reciprocity motif]  \\\n",
+       "e5hm9mp                            1.0                       4.0   \n",
+       "e5ytz1d                            1.0                       1.0   \n",
+       "e6ls80j                            1.0                       1.0   \n",
+       "e5mhgl5                            1.0                       2.0   \n",
+       "e6w6fah                            0.0                       0.0   \n",
+       "...                                ...                       ...   \n",
+       "e65ca8k                            1.0                       7.0   \n",
+       "e6cdkpy                            0.0                       0.0   \n",
+       "e5wc4tj                            1.0                       8.0   \n",
+       "e6ua0sb                            1.0                       3.0   \n",
+       "e5ua84v                            1.0                       3.0   \n",
        "\n",
-       "         entropy[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                1.676988   \n",
-       "e5ywqyk                                1.214890   \n",
-       "e5qv9rj                                2.197225   \n",
-       "e6jhojf                                1.427061   \n",
-       "e6989ii                                0.693147   \n",
-       "e69lgse                                1.889159   \n",
-       "e5kwkg2                                2.197225   \n",
-       "e6mehe7                                1.676988   \n",
-       "e6m0hsd                                0.936888   \n",
-       "e64r385                                1.889159   \n",
-       "e5surbt                                2.197225   \n",
-       "e58gxii                                1.676988   \n",
-       "e64vc8y                                2.197225   \n",
-       "e57504g                                1.889159   \n",
-       "e5borjq                                2.043192   \n",
-       "e64n9zv                                1.060857   \n",
-       "e582ud3                                2.197225   \n",
-       "e64i9cf                                1.676988   \n",
-       "e6q9204                                1.427061   \n",
-       "e5modd7                                2.197225   \n",
-       "e5xhbyd                                1.310784   \n",
-       "e5oaf7h                                0.936888   \n",
-       "e6nir3u                                0.693147   \n",
-       "e6c3xdn                                2.197225   \n",
-       "e5d3zaa                                1.676988   \n",
-       "e5gnjv9                                2.043192   \n",
-       "e69gw2t                                1.464816   \n",
-       "e5syrih                                1.889159   \n",
-       "e5sa2yf                                0.686962   \n",
-       "e6ai7z5                                1.303092   \n",
+       "         is-present[external reciprocity motif]  \\\n",
+       "e5hm9mp                                     1.0   \n",
+       "e5ytz1d                                     1.0   \n",
+       "e6ls80j                                     1.0   \n",
+       "e5mhgl5                                     1.0   \n",
+       "e6w6fah                                     0.0   \n",
        "...                                         ...   \n",
-       "e5smhzk                                0.964963   \n",
-       "e5v91s0                                2.197225   \n",
-       "e6n6di6                                2.043192   \n",
-       "e6iqq30                                2.197225   \n",
-       "e5bfad7                                2.043192   \n",
-       "e6x5he5                                1.386294   \n",
-       "e6l9uyf                                2.043192   \n",
-       "e57hyr1                                1.735126   \n",
-       "e5b8sj7                                2.043192   \n",
-       "e6nlep7                                2.197225   \n",
-       "e6ltazd                                1.464816   \n",
-       "e57a6qq                                1.464816   \n",
-       "e5qc7eb                                1.735126   \n",
-       "e6hqt5y                                2.043192   \n",
-       "e5ua84v                                1.676988   \n",
-       "e65m7kq                                2.043192   \n",
-       "e5ggtru                                2.043192   \n",
-       "e5pmmig                                1.310784   \n",
-       "e64l6vq                                1.676988   \n",
-       "e6fjx0d                                0.964963   \n",
-       "e5h3xyy                                2.043192   \n",
-       "e589ri5                                2.197225   \n",
-       "e5beuqa                                1.427061   \n",
-       "e5lqoj1                                1.676988   \n",
-       "e5kvch1                                1.735126   \n",
-       "e6srvwm                                2.043192   \n",
-       "e5o65mk                                0.693147   \n",
-       "e647cm8                                2.197225   \n",
-       "e58n526                                2.197225   \n",
-       "e69r2kg                                2.043192   \n",
+       "e65ca8k                                     0.0   \n",
+       "e6cdkpy                                     1.0   \n",
+       "e5wc4tj                                     0.0   \n",
+       "e6ua0sb                                     1.0   \n",
+       "e5ua84v                                     1.0   \n",
        "\n",
-       "         is-present[dyadic interaction motif over mid-thread]  \\\n",
-       "e6p7yrp                                                1.0      \n",
-       "e5ywqyk                                                1.0      \n",
-       "e5qv9rj                                                0.0      \n",
-       "e6jhojf                                                1.0      \n",
-       "e6989ii                                                1.0      \n",
-       "e69lgse                                                1.0      \n",
-       "e5kwkg2                                                0.0      \n",
-       "e6mehe7                                                1.0      \n",
-       "e6m0hsd                                                1.0      \n",
-       "e64r385                                                1.0      \n",
-       "e5surbt                                                0.0      \n",
-       "e58gxii                                                1.0      \n",
-       "e64vc8y                                                0.0      \n",
-       "e57504g                                                1.0      \n",
-       "e5borjq                                                1.0      \n",
-       "e64n9zv                                                1.0      \n",
-       "e582ud3                                                0.0      \n",
-       "e64i9cf                                                1.0      \n",
-       "e6q9204                                                1.0      \n",
-       "e5modd7                                                0.0      \n",
-       "e5xhbyd                                                1.0      \n",
-       "e5oaf7h                                                1.0      \n",
-       "e6nir3u                                                1.0      \n",
-       "e6c3xdn                                                0.0      \n",
-       "e5d3zaa                                                1.0      \n",
-       "e5gnjv9                                                0.0      \n",
-       "e69gw2t                                                1.0      \n",
-       "e5syrih                                                1.0      \n",
-       "e5sa2yf                                                1.0      \n",
-       "e6ai7z5                                                1.0      \n",
-       "...                                                    ...      \n",
-       "e5smhzk                                                1.0      \n",
-       "e5v91s0                                                0.0      \n",
-       "e6n6di6                                                1.0      \n",
-       "e6iqq30                                                0.0      \n",
-       "e5bfad7                                                0.0      \n",
-       "e6x5he5                                                0.0      \n",
-       "e6l9uyf                                                0.0      \n",
-       "e57hyr1                                                1.0      \n",
-       "e5b8sj7                                                1.0      \n",
-       "e6nlep7                                                0.0      \n",
-       "e6ltazd                                                1.0      \n",
-       "e57a6qq                                                1.0      \n",
-       "e5qc7eb                                                1.0      \n",
-       "e6hqt5y                                                0.0      \n",
-       "e5ua84v                                                1.0      \n",
-       "e65m7kq                                                1.0      \n",
-       "e5ggtru                                                0.0      \n",
-       "e5pmmig                                                1.0      \n",
-       "e64l6vq                                                1.0      \n",
-       "e6fjx0d                                                1.0      \n",
-       "e5h3xyy                                                1.0      \n",
-       "e589ri5                                                0.0      \n",
-       "e5beuqa                                                1.0      \n",
-       "e5lqoj1                                                1.0      \n",
-       "e5kvch1                                                1.0      \n",
-       "e6srvwm                                                1.0      \n",
-       "e5o65mk                                                1.0      \n",
-       "e647cm8                                                0.0      \n",
-       "e58n526                                                0.0      \n",
-       "e69r2kg                                                1.0      \n",
+       "         count[external reciprocity motif]  \\\n",
+       "e5hm9mp                                4.0   \n",
+       "e5ytz1d                                5.0   \n",
+       "e6ls80j                                4.0   \n",
+       "e5mhgl5                                6.0   \n",
+       "e6w6fah                                0.0   \n",
+       "...                                    ...   \n",
+       "e65ca8k                                0.0   \n",
+       "e6cdkpy                                5.0   \n",
+       "e5wc4tj                                0.0   \n",
+       "e6ua0sb                                4.0   \n",
+       "e5ua84v                                5.0   \n",
        "\n",
        "         is-present[dyadic interaction motif]  \\\n",
-       "e6p7yrp                                   1.0   \n",
-       "e5ywqyk                                   1.0   \n",
-       "e5qv9rj                                   0.0   \n",
-       "e6jhojf                                   1.0   \n",
-       "e6989ii                                   1.0   \n",
-       "e69lgse                                   1.0   \n",
-       "e5kwkg2                                   0.0   \n",
-       "e6mehe7                                   1.0   \n",
-       "e6m0hsd                                   1.0   \n",
-       "e64r385                                   1.0   \n",
-       "e5surbt                                   0.0   \n",
-       "e58gxii                                   1.0   \n",
-       "e64vc8y                                   0.0   \n",
-       "e57504g                                   1.0   \n",
-       "e5borjq                                   1.0   \n",
-       "e64n9zv                                   1.0   \n",
-       "e582ud3                                   0.0   \n",
-       "e64i9cf                                   1.0   \n",
-       "e6q9204                                   1.0   \n",
-       "e5modd7                                   0.0   \n",
-       "e5xhbyd                                   1.0   \n",
-       "e5oaf7h                                   1.0   \n",
-       "e6nir3u                                   1.0   \n",
-       "e6c3xdn                                   0.0   \n",
-       "e5d3zaa                                   1.0   \n",
-       "e5gnjv9                                   0.0   \n",
-       "e69gw2t                                   1.0   \n",
-       "e5syrih                                   1.0   \n",
-       "e5sa2yf                                   1.0   \n",
-       "e6ai7z5                                   1.0   \n",
+       "e5hm9mp                                   1.0   \n",
+       "e5ytz1d                                   1.0   \n",
+       "e6ls80j                                   1.0   \n",
+       "e5mhgl5                                   1.0   \n",
+       "e6w6fah                                   0.0   \n",
        "...                                       ...   \n",
-       "e5smhzk                                   1.0   \n",
-       "e5v91s0                                   0.0   \n",
-       "e6n6di6                                   1.0   \n",
-       "e6iqq30                                   1.0   \n",
-       "e5bfad7                                   1.0   \n",
-       "e6x5he5                                   1.0   \n",
-       "e6l9uyf                                   0.0   \n",
-       "e57hyr1                                   1.0   \n",
-       "e5b8sj7                                   1.0   \n",
-       "e6nlep7                                   0.0   \n",
-       "e6ltazd                                   1.0   \n",
-       "e57a6qq                                   1.0   \n",
-       "e5qc7eb                                   1.0   \n",
-       "e6hqt5y                                   0.0   \n",
+       "e65ca8k                                   0.0   \n",
+       "e6cdkpy                                   0.0   \n",
+       "e5wc4tj                                   1.0   \n",
+       "e6ua0sb                                   1.0   \n",
        "e5ua84v                                   1.0   \n",
-       "e65m7kq                                   1.0   \n",
-       "e5ggtru                                   0.0   \n",
-       "e5pmmig                                   1.0   \n",
-       "e64l6vq                                   1.0   \n",
-       "e6fjx0d                                   1.0   \n",
-       "e5h3xyy                                   1.0   \n",
-       "e589ri5                                   0.0   \n",
-       "e5beuqa                                   1.0   \n",
-       "e5lqoj1                                   1.0   \n",
-       "e5kvch1                                   1.0   \n",
-       "e6srvwm                                   1.0   \n",
-       "e5o65mk                                   1.0   \n",
-       "e647cm8                                   1.0   \n",
-       "e58n526                                   0.0   \n",
-       "e69r2kg                                   1.0   \n",
        "\n",
-       "         is-present[external reciprocity motif over mid-thread]  \\\n",
-       "e6p7yrp                                                1.0        \n",
-       "e5ywqyk                                                1.0        \n",
-       "e5qv9rj                                                1.0        \n",
-       "e6jhojf                                                1.0        \n",
-       "e6989ii                                                0.0        \n",
-       "e69lgse                                                1.0        \n",
-       "e5kwkg2                                                1.0        \n",
-       "e6mehe7                                                1.0        \n",
-       "e6m0hsd                                                0.0        \n",
-       "e64r385                                                1.0        \n",
-       "e5surbt                                                1.0        \n",
-       "e58gxii                                                1.0        \n",
-       "e64vc8y                                                1.0        \n",
-       "e57504g                                                1.0        \n",
-       "e5borjq                                                1.0        \n",
-       "e64n9zv                                                1.0        \n",
-       "e582ud3                                                0.0        \n",
-       "e64i9cf                                                0.0        \n",
-       "e6q9204                                                1.0        \n",
-       "e5modd7                                                1.0        \n",
-       "e5xhbyd                                                1.0        \n",
-       "e5oaf7h                                                1.0        \n",
-       "e6nir3u                                                0.0        \n",
-       "e6c3xdn                                                1.0        \n",
-       "e5d3zaa                                                1.0        \n",
-       "e5gnjv9                                                0.0        \n",
-       "e69gw2t                                                1.0        \n",
-       "e5syrih                                                1.0        \n",
-       "e5sa2yf                                                0.0        \n",
-       "e6ai7z5                                                1.0        \n",
-       "...                                                    ...        \n",
-       "e5smhzk                                                0.0        \n",
-       "e5v91s0                                                1.0        \n",
-       "e6n6di6                                                1.0        \n",
-       "e6iqq30                                                0.0        \n",
-       "e5bfad7                                                1.0        \n",
-       "e6x5he5                                                0.0        \n",
-       "e6l9uyf                                                1.0        \n",
-       "e57hyr1                                                1.0        \n",
-       "e5b8sj7                                                1.0        \n",
-       "e6nlep7                                                0.0        \n",
-       "e6ltazd                                                0.0        \n",
-       "e57a6qq                                                1.0        \n",
-       "e5qc7eb                                                1.0        \n",
-       "e6hqt5y                                                0.0        \n",
-       "e5ua84v                                                1.0        \n",
-       "e65m7kq                                                1.0        \n",
-       "e5ggtru                                                1.0        \n",
-       "e5pmmig                                                1.0        \n",
-       "e64l6vq                                                0.0        \n",
-       "e6fjx0d                                                0.0        \n",
-       "e5h3xyy                                                1.0        \n",
-       "e589ri5                                                1.0        \n",
-       "e5beuqa                                                1.0        \n",
-       "e5lqoj1                                                0.0        \n",
-       "e5kvch1                                                1.0        \n",
-       "e6srvwm                                                1.0        \n",
-       "e5o65mk                                                0.0        \n",
-       "e647cm8                                                1.0        \n",
-       "e58n526                                                0.0        \n",
-       "e69r2kg                                                1.0        \n",
+       "         count[dyadic interaction motif]  is-present[incoming triads]  \\\n",
+       "e5hm9mp                              3.0                          1.0   \n",
+       "e5ytz1d                              1.0                          1.0   \n",
+       "e6ls80j                              1.0                          1.0   \n",
+       "e5mhgl5                              1.0                          1.0   \n",
+       "e6w6fah                              0.0                          1.0   \n",
+       "...                                  ...                          ...   \n",
+       "e65ca8k                              0.0                          1.0   \n",
+       "e6cdkpy                              0.0                          1.0   \n",
+       "e5wc4tj                              1.0                          0.0   \n",
+       "e6ua0sb                              2.0                          1.0   \n",
+       "e5ua84v                              3.0                          1.0   \n",
+       "\n",
+       "         count[incoming triads]  is-present[outgoing triads]  \\\n",
+       "e5hm9mp                     4.0                          1.0   \n",
+       "e5ytz1d                     7.0                          0.0   \n",
+       "e6ls80j                     9.0                          1.0   \n",
+       "e5mhgl5                     2.0                          1.0   \n",
+       "e6w6fah                    28.0                          0.0   \n",
+       "...                         ...                          ...   \n",
+       "e65ca8k                     1.0                          0.0   \n",
+       "e6cdkpy                     8.0                          0.0   \n",
+       "e5wc4tj                     0.0                          0.0   \n",
+       "e6ua0sb                     6.0                          1.0   \n",
+       "e5ua84v                     7.0                          1.0   \n",
+       "\n",
+       "         count[outgoing triads]  max[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                     3.0                                           3.0   \n",
+       "e5ytz1d                     0.0                                           3.0   \n",
+       "e6ls80j                     4.0                                           3.0   \n",
+       "e5mhgl5                     1.0                                           2.0   \n",
+       "e6w6fah                     0.0                                           0.0   \n",
+       "...                         ...                                           ...   \n",
+       "e65ca8k                     0.0                                           1.0   \n",
+       "e6cdkpy                     0.0                                           2.0   \n",
+       "e5wc4tj                     0.0                                           1.0   \n",
+       "e6ua0sb                     2.0                                           4.0   \n",
+       "e5ua84v                     4.0                                           3.0   \n",
        "\n",
-       "         is-present[external reciprocity motif]  \\\n",
-       "e6p7yrp                                     1.0   \n",
-       "e5ywqyk                                     1.0   \n",
-       "e5qv9rj                                     1.0   \n",
-       "e6jhojf                                     1.0   \n",
-       "e6989ii                                     0.0   \n",
-       "e69lgse                                     1.0   \n",
-       "e5kwkg2                                     1.0   \n",
-       "e6mehe7                                     1.0   \n",
-       "e6m0hsd                                     1.0   \n",
-       "e64r385                                     1.0   \n",
-       "e5surbt                                     1.0   \n",
-       "e58gxii                                     1.0   \n",
-       "e64vc8y                                     1.0   \n",
-       "e57504g                                     1.0   \n",
-       "e5borjq                                     1.0   \n",
-       "e64n9zv                                     1.0   \n",
-       "e582ud3                                     1.0   \n",
-       "e64i9cf                                     1.0   \n",
-       "e6q9204                                     1.0   \n",
-       "e5modd7                                     1.0   \n",
-       "e5xhbyd                                     1.0   \n",
-       "e5oaf7h                                     1.0   \n",
-       "e6nir3u                                     0.0   \n",
-       "e6c3xdn                                     1.0   \n",
-       "e5d3zaa                                     1.0   \n",
-       "e5gnjv9                                     1.0   \n",
-       "e69gw2t                                     1.0   \n",
-       "e5syrih                                     1.0   \n",
-       "e5sa2yf                                     0.0   \n",
-       "e6ai7z5                                     1.0   \n",
-       "...                                         ...   \n",
-       "e5smhzk                                     0.0   \n",
-       "e5v91s0                                     1.0   \n",
-       "e6n6di6                                     1.0   \n",
-       "e6iqq30                                     1.0   \n",
-       "e5bfad7                                     1.0   \n",
-       "e6x5he5                                     0.0   \n",
-       "e6l9uyf                                     1.0   \n",
-       "e57hyr1                                     1.0   \n",
-       "e5b8sj7                                     1.0   \n",
-       "e6nlep7                                     0.0   \n",
-       "e6ltazd                                     1.0   \n",
-       "e57a6qq                                     1.0   \n",
-       "e5qc7eb                                     1.0   \n",
-       "e6hqt5y                                     1.0   \n",
-       "e5ua84v                                     1.0   \n",
-       "e65m7kq                                     1.0   \n",
-       "e5ggtru                                     1.0   \n",
-       "e5pmmig                                     1.0   \n",
-       "e64l6vq                                     1.0   \n",
-       "e6fjx0d                                     1.0   \n",
-       "e5h3xyy                                     1.0   \n",
-       "e589ri5                                     1.0   \n",
-       "e5beuqa                                     1.0   \n",
-       "e5lqoj1                                     1.0   \n",
-       "e5kvch1                                     1.0   \n",
-       "e6srvwm                                     1.0   \n",
-       "e5o65mk                                     0.0   \n",
-       "e647cm8                                     1.0   \n",
-       "e58n526                                     0.0   \n",
-       "e69r2kg                                     1.0   \n",
+       "         argmax[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                              0.0   \n",
+       "e5ytz1d                                              1.0   \n",
+       "e6ls80j                                              1.0   \n",
+       "e5mhgl5                                              0.0   \n",
+       "e6w6fah                                              0.0   \n",
+       "...                                                  ...   \n",
+       "e65ca8k                                              1.0   \n",
+       "e6cdkpy                                              0.0   \n",
+       "e5wc4tj                                              0.0   \n",
+       "e6ua0sb                                              1.0   \n",
+       "e5ua84v                                              0.0   \n",
        "\n",
-       "         is-present[incoming triads over mid-thread]  \\\n",
-       "e6p7yrp                                          1.0   \n",
-       "e5ywqyk                                          1.0   \n",
-       "e5qv9rj                                          1.0   \n",
-       "e6jhojf                                          1.0   \n",
-       "e6989ii                                          0.0   \n",
-       "e69lgse                                          1.0   \n",
-       "e5kwkg2                                          1.0   \n",
-       "e6mehe7                                          1.0   \n",
-       "e6m0hsd                                          1.0   \n",
-       "e64r385                                          1.0   \n",
-       "e5surbt                                          0.0   \n",
-       "e58gxii                                          1.0   \n",
-       "e64vc8y                                          0.0   \n",
-       "e57504g                                          1.0   \n",
-       "e5borjq                                          1.0   \n",
-       "e64n9zv                                          1.0   \n",
-       "e582ud3                                          1.0   \n",
-       "e64i9cf                                          1.0   \n",
-       "e6q9204                                          1.0   \n",
-       "e5modd7                                          1.0   \n",
-       "e5xhbyd                                          1.0   \n",
-       "e5oaf7h                                          1.0   \n",
-       "e6nir3u                                          0.0   \n",
-       "e6c3xdn                                          1.0   \n",
-       "e5d3zaa                                          1.0   \n",
-       "e5gnjv9                                          0.0   \n",
-       "e69gw2t                                          1.0   \n",
-       "e5syrih                                          1.0   \n",
-       "e5sa2yf                                          0.0   \n",
-       "e6ai7z5                                          1.0   \n",
-       "...                                              ...   \n",
-       "e5smhzk                                          0.0   \n",
-       "e5v91s0                                          1.0   \n",
-       "e6n6di6                                          1.0   \n",
-       "e6iqq30                                          0.0   \n",
-       "e5bfad7                                          1.0   \n",
-       "e6x5he5                                          0.0   \n",
-       "e6l9uyf                                          1.0   \n",
-       "e57hyr1                                          1.0   \n",
-       "e5b8sj7                                          1.0   \n",
-       "e6nlep7                                          0.0   \n",
-       "e6ltazd                                          1.0   \n",
-       "e57a6qq                                          1.0   \n",
-       "e5qc7eb                                          1.0   \n",
-       "e6hqt5y                                          1.0   \n",
-       "e5ua84v                                          1.0   \n",
-       "e65m7kq                                          1.0   \n",
-       "e5ggtru                                          1.0   \n",
-       "e5pmmig                                          1.0   \n",
-       "e64l6vq                                          1.0   \n",
-       "e6fjx0d                                          0.0   \n",
-       "e5h3xyy                                          1.0   \n",
-       "e589ri5                                          0.0   \n",
-       "e5beuqa                                          1.0   \n",
-       "e5lqoj1                                          0.0   \n",
-       "e5kvch1                                          1.0   \n",
-       "e6srvwm                                          1.0   \n",
-       "e5o65mk                                          0.0   \n",
-       "e647cm8                                          1.0   \n",
-       "e58n526                                          0.0   \n",
-       "e69r2kg                                          1.0   \n",
-       "\n",
-       "         is-present[incoming triads]  \\\n",
-       "e6p7yrp                          1.0   \n",
-       "e5ywqyk                          1.0   \n",
-       "e5qv9rj                          1.0   \n",
-       "e6jhojf                          1.0   \n",
-       "e6989ii                          0.0   \n",
-       "e69lgse                          1.0   \n",
-       "e5kwkg2                          1.0   \n",
-       "e6mehe7                          1.0   \n",
-       "e6m0hsd                          1.0   \n",
-       "e64r385                          1.0   \n",
-       "e5surbt                          1.0   \n",
-       "e58gxii                          1.0   \n",
-       "e64vc8y                          1.0   \n",
-       "e57504g                          1.0   \n",
-       "e5borjq                          1.0   \n",
-       "e64n9zv                          1.0   \n",
-       "e582ud3                          1.0   \n",
-       "e64i9cf                          1.0   \n",
-       "e6q9204                          1.0   \n",
-       "e5modd7                          1.0   \n",
-       "e5xhbyd                          1.0   \n",
-       "e5oaf7h                          1.0   \n",
-       "e6nir3u                          0.0   \n",
-       "e6c3xdn                          1.0   \n",
-       "e5d3zaa                          1.0   \n",
-       "e5gnjv9                          1.0   \n",
-       "e69gw2t                          1.0   \n",
-       "e5syrih                          1.0   \n",
-       "e5sa2yf                          0.0   \n",
-       "e6ai7z5                          1.0   \n",
-       "...                              ...   \n",
-       "e5smhzk                          1.0   \n",
-       "e5v91s0                          1.0   \n",
-       "e6n6di6                          1.0   \n",
-       "e6iqq30                          1.0   \n",
-       "e5bfad7                          1.0   \n",
-       "e6x5he5                          1.0   \n",
-       "e6l9uyf                          1.0   \n",
-       "e57hyr1                          1.0   \n",
-       "e5b8sj7                          1.0   \n",
-       "e6nlep7                          1.0   \n",
-       "e6ltazd                          1.0   \n",
-       "e57a6qq                          1.0   \n",
-       "e5qc7eb                          1.0   \n",
-       "e6hqt5y                          1.0   \n",
-       "e5ua84v                          1.0   \n",
-       "e65m7kq                          1.0   \n",
-       "e5ggtru                          1.0   \n",
-       "e5pmmig                          1.0   \n",
-       "e64l6vq                          1.0   \n",
-       "e6fjx0d                          1.0   \n",
-       "e5h3xyy                          1.0   \n",
-       "e589ri5                          1.0   \n",
-       "e5beuqa                          1.0   \n",
-       "e5lqoj1                          1.0   \n",
-       "e5kvch1                          1.0   \n",
-       "e6srvwm                          1.0   \n",
-       "e5o65mk                          0.0   \n",
-       "e647cm8                          1.0   \n",
-       "e58n526                          1.0   \n",
-       "e69r2kg                          1.0   \n",
+       "         norm.max[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.375000   \n",
+       "e5ytz1d                                           0.500000   \n",
+       "e6ls80j                                           0.600000   \n",
+       "e5mhgl5                                           0.250000   \n",
+       "e6w6fah                                           0.000000   \n",
+       "...                                                    ...   \n",
+       "e65ca8k                                           0.142857   \n",
+       "e6cdkpy                                           0.400000   \n",
+       "e5wc4tj                                           0.125000   \n",
+       "e6ua0sb                                           0.571429   \n",
+       "e5ua84v                                           0.375000   \n",
        "\n",
-       "         is-present[outgoing triads over mid-thread]  \\\n",
-       "e6p7yrp                                          1.0   \n",
-       "e5ywqyk                                          1.0   \n",
-       "e5qv9rj                                          0.0   \n",
-       "e6jhojf                                          1.0   \n",
-       "e6989ii                                          0.0   \n",
-       "e69lgse                                          1.0   \n",
-       "e5kwkg2                                          0.0   \n",
-       "e6mehe7                                          1.0   \n",
-       "e6m0hsd                                          1.0   \n",
-       "e64r385                                          1.0   \n",
-       "e5surbt                                          0.0   \n",
-       "e58gxii                                          1.0   \n",
-       "e64vc8y                                          0.0   \n",
-       "e57504g                                          1.0   \n",
-       "e5borjq                                          0.0   \n",
-       "e64n9zv                                          1.0   \n",
-       "e582ud3                                          0.0   \n",
-       "e64i9cf                                          1.0   \n",
-       "e6q9204                                          1.0   \n",
-       "e5modd7                                          0.0   \n",
-       "e5xhbyd                                          1.0   \n",
-       "e5oaf7h                                          1.0   \n",
-       "e6nir3u                                          0.0   \n",
-       "e6c3xdn                                          0.0   \n",
-       "e5d3zaa                                          0.0   \n",
-       "e5gnjv9                                          0.0   \n",
-       "e69gw2t                                          1.0   \n",
-       "e5syrih                                          1.0   \n",
-       "e5sa2yf                                          0.0   \n",
-       "e6ai7z5                                          1.0   \n",
-       "...                                              ...   \n",
-       "e5smhzk                                          1.0   \n",
-       "e5v91s0                                          0.0   \n",
-       "e6n6di6                                          1.0   \n",
-       "e6iqq30                                          0.0   \n",
-       "e5bfad7                                          1.0   \n",
-       "e6x5he5                                          1.0   \n",
-       "e6l9uyf                                          0.0   \n",
-       "e57hyr1                                          0.0   \n",
-       "e5b8sj7                                          0.0   \n",
-       "e6nlep7                                          0.0   \n",
-       "e6ltazd                                          0.0   \n",
-       "e57a6qq                                          1.0   \n",
-       "e5qc7eb                                          0.0   \n",
-       "e6hqt5y                                          0.0   \n",
-       "e5ua84v                                          1.0   \n",
-       "e65m7kq                                          0.0   \n",
-       "e5ggtru                                          0.0   \n",
-       "e5pmmig                                          1.0   \n",
-       "e64l6vq                                          1.0   \n",
-       "e6fjx0d                                          0.0   \n",
-       "e5h3xyy                                          0.0   \n",
-       "e589ri5                                          0.0   \n",
-       "e5beuqa                                          1.0   \n",
-       "e5lqoj1                                          1.0   \n",
-       "e5kvch1                                          0.0   \n",
-       "e6srvwm                                          0.0   \n",
-       "e5o65mk                                          0.0   \n",
-       "e647cm8                                          0.0   \n",
-       "e58n526                                          0.0   \n",
-       "e69r2kg                                          1.0   \n",
-       "\n",
-       "         is-present[outgoing triads]  \\\n",
-       "e6p7yrp                          1.0   \n",
-       "e5ywqyk                          1.0   \n",
-       "e5qv9rj                          0.0   \n",
-       "e6jhojf                          1.0   \n",
-       "e6989ii                          0.0   \n",
-       "e69lgse                          1.0   \n",
-       "e5kwkg2                          0.0   \n",
-       "e6mehe7                          1.0   \n",
-       "e6m0hsd                          1.0   \n",
-       "e64r385                          1.0   \n",
-       "e5surbt                          0.0   \n",
-       "e58gxii                          1.0   \n",
-       "e64vc8y                          0.0   \n",
-       "e57504g                          1.0   \n",
-       "e5borjq                          1.0   \n",
-       "e64n9zv                          1.0   \n",
-       "e582ud3                          0.0   \n",
-       "e64i9cf                          1.0   \n",
-       "e6q9204                          1.0   \n",
-       "e5modd7                          0.0   \n",
-       "e5xhbyd                          1.0   \n",
-       "e5oaf7h                          1.0   \n",
-       "e6nir3u                          0.0   \n",
-       "e6c3xdn                          0.0   \n",
-       "e5d3zaa                          1.0   \n",
-       "e5gnjv9                          1.0   \n",
-       "e69gw2t                          1.0   \n",
-       "e5syrih                          1.0   \n",
-       "e5sa2yf                          0.0   \n",
-       "e6ai7z5                          1.0   \n",
-       "...                              ...   \n",
-       "e5smhzk                          1.0   \n",
-       "e5v91s0                          0.0   \n",
-       "e6n6di6                          1.0   \n",
-       "e6iqq30                          0.0   \n",
-       "e5bfad7                          1.0   \n",
-       "e6x5he5                          1.0   \n",
-       "e6l9uyf                          1.0   \n",
-       "e57hyr1                          1.0   \n",
-       "e5b8sj7                          1.0   \n",
-       "e6nlep7                          0.0   \n",
-       "e6ltazd                          1.0   \n",
-       "e57a6qq                          1.0   \n",
-       "e5qc7eb                          1.0   \n",
-       "e6hqt5y                          1.0   \n",
-       "e5ua84v                          1.0   \n",
-       "e65m7kq                          1.0   \n",
-       "e5ggtru                          1.0   \n",
-       "e5pmmig                          1.0   \n",
-       "e64l6vq                          1.0   \n",
-       "e6fjx0d                          1.0   \n",
-       "e5h3xyy                          1.0   \n",
-       "e589ri5                          0.0   \n",
-       "e5beuqa                          1.0   \n",
-       "e5lqoj1                          1.0   \n",
-       "e5kvch1                          1.0   \n",
-       "e6srvwm                          1.0   \n",
-       "e5o65mk                          0.0   \n",
-       "e647cm8                          0.0   \n",
-       "e58n526                          0.0   \n",
-       "e69r2kg                          1.0   \n",
+       "         2nd-largest[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0      \n",
+       "e5ytz1d                                                2.0      \n",
+       "e6ls80j                                                1.0      \n",
+       "e5mhgl5                                                2.0      \n",
+       "e6w6fah                                                0.0      \n",
+       "...                                                    ...      \n",
+       "e65ca8k                                                1.0      \n",
+       "e6cdkpy                                                2.0      \n",
+       "e5wc4tj                                                1.0      \n",
+       "e6ua0sb                                                1.0      \n",
+       "e5ua84v                                                2.0      \n",
        "\n",
-       "         is-present[reciprocity motif over mid-thread]  \\\n",
-       "e6p7yrp                                            1.0   \n",
-       "e5ywqyk                                            1.0   \n",
-       "e5qv9rj                                            0.0   \n",
-       "e6jhojf                                            1.0   \n",
-       "e6989ii                                            1.0   \n",
-       "e69lgse                                            1.0   \n",
-       "e5kwkg2                                            0.0   \n",
-       "e6mehe7                                            1.0   \n",
-       "e6m0hsd                                            1.0   \n",
-       "e64r385                                            1.0   \n",
-       "e5surbt                                            0.0   \n",
-       "e58gxii                                            1.0   \n",
-       "e64vc8y                                            0.0   \n",
-       "e57504g                                            1.0   \n",
-       "e5borjq                                            1.0   \n",
-       "e64n9zv                                            1.0   \n",
-       "e582ud3                                            0.0   \n",
-       "e64i9cf                                            1.0   \n",
-       "e6q9204                                            1.0   \n",
-       "e5modd7                                            0.0   \n",
-       "e5xhbyd                                            1.0   \n",
-       "e5oaf7h                                            1.0   \n",
-       "e6nir3u                                            1.0   \n",
-       "e6c3xdn                                            0.0   \n",
-       "e5d3zaa                                            1.0   \n",
-       "e5gnjv9                                            0.0   \n",
-       "e69gw2t                                            1.0   \n",
-       "e5syrih                                            1.0   \n",
-       "e5sa2yf                                            1.0   \n",
-       "e6ai7z5                                            1.0   \n",
-       "...                                                ...   \n",
-       "e5smhzk                                            1.0   \n",
-       "e5v91s0                                            0.0   \n",
-       "e6n6di6                                            1.0   \n",
-       "e6iqq30                                            0.0   \n",
-       "e5bfad7                                            0.0   \n",
-       "e6x5he5                                            0.0   \n",
-       "e6l9uyf                                            0.0   \n",
-       "e57hyr1                                            1.0   \n",
-       "e5b8sj7                                            1.0   \n",
-       "e6nlep7                                            0.0   \n",
-       "e6ltazd                                            1.0   \n",
-       "e57a6qq                                            1.0   \n",
-       "e5qc7eb                                            1.0   \n",
-       "e6hqt5y                                            0.0   \n",
-       "e5ua84v                                            1.0   \n",
-       "e65m7kq                                            1.0   \n",
-       "e5ggtru                                            0.0   \n",
-       "e5pmmig                                            1.0   \n",
-       "e64l6vq                                            1.0   \n",
-       "e6fjx0d                                            1.0   \n",
-       "e5h3xyy                                            1.0   \n",
-       "e589ri5                                            0.0   \n",
-       "e5beuqa                                            1.0   \n",
-       "e5lqoj1                                            1.0   \n",
-       "e5kvch1                                            1.0   \n",
-       "e6srvwm                                            1.0   \n",
-       "e5o65mk                                            1.0   \n",
-       "e647cm8                                            0.0   \n",
-       "e58n526                                            0.0   \n",
-       "e69r2kg                                            1.0   \n",
-       "\n",
-       "         is-present[reciprocity motif]  \\\n",
-       "e6p7yrp                            1.0   \n",
-       "e5ywqyk                            1.0   \n",
-       "e5qv9rj                            0.0   \n",
-       "e6jhojf                            1.0   \n",
-       "e6989ii                            1.0   \n",
-       "e69lgse                            1.0   \n",
-       "e5kwkg2                            0.0   \n",
-       "e6mehe7                            1.0   \n",
-       "e6m0hsd                            1.0   \n",
-       "e64r385                            1.0   \n",
-       "e5surbt                            0.0   \n",
-       "e58gxii                            1.0   \n",
-       "e64vc8y                            0.0   \n",
-       "e57504g                            1.0   \n",
-       "e5borjq                            1.0   \n",
-       "e64n9zv                            1.0   \n",
-       "e582ud3                            0.0   \n",
-       "e64i9cf                            1.0   \n",
-       "e6q9204                            1.0   \n",
-       "e5modd7                            0.0   \n",
-       "e5xhbyd                            1.0   \n",
-       "e5oaf7h                            1.0   \n",
-       "e6nir3u                            1.0   \n",
-       "e6c3xdn                            0.0   \n",
-       "e5d3zaa                            1.0   \n",
-       "e5gnjv9                            0.0   \n",
-       "e69gw2t                            1.0   \n",
-       "e5syrih                            1.0   \n",
-       "e5sa2yf                            1.0   \n",
-       "e6ai7z5                            1.0   \n",
-       "...                                ...   \n",
-       "e5smhzk                            1.0   \n",
-       "e5v91s0                            0.0   \n",
-       "e6n6di6                            1.0   \n",
-       "e6iqq30                            1.0   \n",
-       "e5bfad7                            1.0   \n",
-       "e6x5he5                            1.0   \n",
-       "e6l9uyf                            0.0   \n",
-       "e57hyr1                            1.0   \n",
-       "e5b8sj7                            1.0   \n",
-       "e6nlep7                            0.0   \n",
-       "e6ltazd                            1.0   \n",
-       "e57a6qq                            1.0   \n",
-       "e5qc7eb                            1.0   \n",
-       "e6hqt5y                            0.0   \n",
-       "e5ua84v                            1.0   \n",
-       "e65m7kq                            1.0   \n",
-       "e5ggtru                            0.0   \n",
-       "e5pmmig                            1.0   \n",
-       "e64l6vq                            1.0   \n",
-       "e6fjx0d                            1.0   \n",
-       "e5h3xyy                            1.0   \n",
-       "e589ri5                            0.0   \n",
-       "e5beuqa                            1.0   \n",
-       "e5lqoj1                            1.0   \n",
-       "e5kvch1                            1.0   \n",
-       "e6srvwm                            1.0   \n",
-       "e5o65mk                            1.0   \n",
-       "e647cm8                            1.0   \n",
-       "e58n526                            0.0   \n",
-       "e69r2kg                            1.0   \n",
+       "         2nd-argmax[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0     \n",
+       "e5ytz1d                                                0.0     \n",
+       "e6ls80j                                                4.0     \n",
+       "e5mhgl5                                                3.0     \n",
+       "e6w6fah                                                1.0     \n",
+       "...                                                    ...     \n",
+       "e65ca8k                                                2.0     \n",
+       "e6cdkpy                                                1.0     \n",
+       "e5wc4tj                                                1.0     \n",
+       "e6ua0sb                                                0.0     \n",
+       "e5ua84v                                                4.0     \n",
        "\n",
-       "         max[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           3.0   \n",
-       "e5ywqyk                                           2.0   \n",
-       "e5qv9rj                                           3.0   \n",
-       "e6jhojf                                           3.0   \n",
-       "e6989ii                                           1.0   \n",
-       "e69lgse                                           3.0   \n",
-       "e5kwkg2                                           2.0   \n",
-       "e6mehe7                                           2.0   \n",
-       "e6m0hsd                                           2.0   \n",
-       "e64r385                                           2.0   \n",
-       "e5surbt                                           1.0   \n",
-       "e58gxii                                           3.0   \n",
-       "e64vc8y                                           1.0   \n",
-       "e57504g                                           2.0   \n",
-       "e5borjq                                           3.0   \n",
-       "e64n9zv                                           2.0   \n",
-       "e582ud3                                           2.0   \n",
-       "e64i9cf                                           2.0   \n",
-       "e6q9204                                           3.0   \n",
-       "e5modd7                                           4.0   \n",
-       "e5xhbyd                                           2.0   \n",
-       "e5oaf7h                                           3.0   \n",
-       "e6nir3u                                           1.0   \n",
-       "e6c3xdn                                           2.0   \n",
-       "e5d3zaa                                           2.0   \n",
-       "e5gnjv9                                           1.0   \n",
-       "e69gw2t                                           2.0   \n",
-       "e5syrih                                           4.0   \n",
-       "e5sa2yf                                           1.0   \n",
-       "e6ai7z5                                           2.0   \n",
-       "...                                               ...   \n",
-       "e5smhzk                                           1.0   \n",
-       "e5v91s0                                           2.0   \n",
-       "e6n6di6                                           4.0   \n",
-       "e6iqq30                                           1.0   \n",
-       "e5bfad7                                           2.0   \n",
-       "e6x5he5                                           1.0   \n",
-       "e6l9uyf                                           2.0   \n",
-       "e57hyr1                                           2.0   \n",
-       "e5b8sj7                                           4.0   \n",
-       "e6nlep7                                           0.0   \n",
-       "e6ltazd                                           4.0   \n",
-       "e57a6qq                                           3.0   \n",
-       "e5qc7eb                                           3.0   \n",
-       "e6hqt5y                                           4.0   \n",
-       "e5ua84v                                           4.0   \n",
-       "e65m7kq                                           3.0   \n",
-       "e5ggtru                                           5.0   \n",
-       "e5pmmig                                           2.0   \n",
-       "e64l6vq                                           2.0   \n",
-       "e6fjx0d                                           1.0   \n",
-       "e5h3xyy                                           2.0   \n",
-       "e589ri5                                           1.0   \n",
-       "e5beuqa                                           4.0   \n",
-       "e5lqoj1                                           1.0   \n",
-       "e5kvch1                                           2.0   \n",
-       "e6srvwm                                           2.0   \n",
-       "e5o65mk                                           1.0   \n",
-       "e647cm8                                           3.0   \n",
-       "e58n526                                           0.0   \n",
-       "e69r2kg                                           3.0   \n",
+       "         norm.2nd-largest[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.125000           \n",
+       "e5ytz1d                                           0.333333           \n",
+       "e6ls80j                                           0.200000           \n",
+       "e5mhgl5                                           0.250000           \n",
+       "e6w6fah                                                NaN           \n",
+       "...                                                    ...           \n",
+       "e65ca8k                                           0.142857           \n",
+       "e6cdkpy                                           0.400000           \n",
+       "e5wc4tj                                           0.125000           \n",
+       "e6ua0sb                                           0.142857           \n",
+       "e5ua84v                                           0.250000           \n",
        "\n",
-       "         max[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                5.0   \n",
-       "e5ywqyk                                2.0   \n",
-       "e5qv9rj                                3.0   \n",
-       "e6jhojf                                4.0   \n",
-       "e6989ii                                1.0   \n",
-       "e69lgse                                3.0   \n",
-       "e5kwkg2                                3.0   \n",
-       "e6mehe7                                4.0   \n",
-       "e6m0hsd                                2.0   \n",
-       "e64r385                                2.0   \n",
-       "e5surbt                                5.0   \n",
-       "e58gxii                                4.0   \n",
-       "e64vc8y                                6.0   \n",
-       "e57504g                                2.0   \n",
-       "e5borjq                                3.0   \n",
-       "e64n9zv                                2.0   \n",
-       "e582ud3                                6.0   \n",
-       "e64i9cf                                4.0   \n",
-       "e6q9204                                3.0   \n",
-       "e5modd7                                4.0   \n",
-       "e5xhbyd                                2.0   \n",
-       "e5oaf7h                                3.0   \n",
-       "e6nir3u                                1.0   \n",
-       "e6c3xdn                                2.0   \n",
-       "e5d3zaa                                2.0   \n",
-       "e5gnjv9                                8.0   \n",
-       "e69gw2t                                2.0   \n",
-       "e5syrih                                4.0   \n",
-       "e5sa2yf                                1.0   \n",
-       "e6ai7z5                                3.0   \n",
-       "...                                    ...   \n",
-       "e5smhzk                                2.0   \n",
-       "e5v91s0                                5.0   \n",
-       "e6n6di6                                4.0   \n",
-       "e6iqq30                                6.0   \n",
-       "e5bfad7                                4.0   \n",
-       "e6x5he5                                4.0   \n",
-       "e6l9uyf                                5.0   \n",
-       "e57hyr1                                4.0   \n",
-       "e5b8sj7                                4.0   \n",
-       "e6nlep7                                9.0   \n",
-       "e6ltazd                                4.0   \n",
-       "e57a6qq                                3.0   \n",
-       "e5qc7eb                                3.0   \n",
-       "e6hqt5y                                4.0   \n",
-       "e5ua84v                                4.0   \n",
-       "e65m7kq                                4.0   \n",
-       "e5ggtru                                5.0   \n",
-       "e5pmmig                                2.0   \n",
-       "e64l6vq                                3.0   \n",
-       "e6fjx0d                                2.0   \n",
-       "e5h3xyy                                4.0   \n",
-       "e589ri5                                6.0   \n",
-       "e5beuqa                                4.0   \n",
-       "e5lqoj1                                5.0   \n",
-       "e5kvch1                                3.0   \n",
-       "e6srvwm                                3.0   \n",
-       "e5o65mk                                1.0   \n",
-       "e647cm8                                4.0   \n",
-       "e58n526                                9.0   \n",
-       "e69r2kg                                3.0   \n",
+       "         mean[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                       0.888889   \n",
+       "e5ytz1d                                       0.666667   \n",
+       "e6ls80j                                       0.555556   \n",
+       "e5mhgl5                                       0.888889   \n",
+       "e6w6fah                                       0.000000   \n",
+       "...                                                ...   \n",
+       "e65ca8k                                       0.777778   \n",
+       "e6cdkpy                                       0.555556   \n",
+       "e5wc4tj                                       0.888889   \n",
+       "e6ua0sb                                       0.777778   \n",
+       "e5ua84v                                       0.888889   \n",
        "\n",
-       "         max[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.0   \n",
-       "e5ywqyk                                           2.0   \n",
-       "e5qv9rj                                           3.0   \n",
-       "e6jhojf                                           2.0   \n",
-       "e6989ii                                           1.0   \n",
-       "e69lgse                                           3.0   \n",
-       "e5kwkg2                                           2.0   \n",
-       "e6mehe7                                           2.0   \n",
-       "e6m0hsd                                           2.0   \n",
-       "e64r385                                           2.0   \n",
-       "e5surbt                                           1.0   \n",
-       "e58gxii                                           2.0   \n",
-       "e64vc8y                                           1.0   \n",
-       "e57504g                                           2.0   \n",
-       "e5borjq                                           3.0   \n",
-       "e64n9zv                                           2.0   \n",
-       "e582ud3                                           2.0   \n",
-       "e64i9cf                                           2.0   \n",
-       "e6q9204                                           2.0   \n",
-       "e5modd7                                           4.0   \n",
-       "e5xhbyd                                           2.0   \n",
-       "e5oaf7h                                           2.0   \n",
-       "e6nir3u                                           1.0   \n",
-       "e6c3xdn                                           2.0   \n",
-       "e5d3zaa                                           2.0   \n",
-       "e5gnjv9                                           1.0   \n",
-       "e69gw2t                                           2.0   \n",
-       "e5syrih                                           3.0   \n",
-       "e5sa2yf                                           1.0   \n",
-       "e6ai7z5                                           1.0   \n",
-       "...                                               ...   \n",
-       "e5smhzk                                           1.0   \n",
-       "e5v91s0                                           2.0   \n",
-       "e6n6di6                                           3.0   \n",
-       "e6iqq30                                           1.0   \n",
-       "e5bfad7                                           2.0   \n",
-       "e6x5he5                                           1.0   \n",
-       "e6l9uyf                                           2.0   \n",
-       "e57hyr1                                           2.0   \n",
-       "e5b8sj7                                           3.0   \n",
-       "e6nlep7                                           0.0   \n",
-       "e6ltazd                                           4.0   \n",
-       "e57a6qq                                           2.0   \n",
-       "e5qc7eb                                           3.0   \n",
-       "e6hqt5y                                           4.0   \n",
-       "e5ua84v                                           3.0   \n",
-       "e65m7kq                                           2.0   \n",
-       "e5ggtru                                           4.0   \n",
-       "e5pmmig                                           2.0   \n",
-       "e64l6vq                                           2.0   \n",
-       "e6fjx0d                                           1.0   \n",
-       "e5h3xyy                                           2.0   \n",
-       "e589ri5                                           1.0   \n",
-       "e5beuqa                                           3.0   \n",
-       "e5lqoj1                                           1.0   \n",
-       "e5kvch1                                           1.0   \n",
-       "e6srvwm                                           2.0   \n",
-       "e5o65mk                                           1.0   \n",
-       "e647cm8                                           3.0   \n",
-       "e58n526                                           0.0   \n",
-       "e69r2kg                                           2.0   \n",
+       "         mean-nonzero[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.333333       \n",
+       "e5ytz1d                                           2.000000       \n",
+       "e6ls80j                                           1.666667       \n",
+       "e5mhgl5                                           1.333333       \n",
+       "e6w6fah                                           0.000000       \n",
+       "...                                                    ...       \n",
+       "e65ca8k                                           1.000000       \n",
+       "e6cdkpy                                           1.666667       \n",
+       "e5wc4tj                                           1.000000       \n",
+       "e6ua0sb                                           1.750000       \n",
+       "e5ua84v                                           1.600000       \n",
        "\n",
-       "         max[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                3.0   \n",
-       "e5ywqyk                                2.0   \n",
-       "e5qv9rj                                3.0   \n",
-       "e6jhojf                                2.0   \n",
-       "e6989ii                                1.0   \n",
-       "e69lgse                                3.0   \n",
-       "e5kwkg2                                3.0   \n",
-       "e6mehe7                                3.0   \n",
-       "e6m0hsd                                2.0   \n",
-       "e64r385                                2.0   \n",
-       "e5surbt                                5.0   \n",
-       "e58gxii                                2.0   \n",
-       "e64vc8y                                6.0   \n",
-       "e57504g                                2.0   \n",
-       "e5borjq                                3.0   \n",
-       "e64n9zv                                2.0   \n",
-       "e582ud3                                6.0   \n",
-       "e64i9cf                                4.0   \n",
-       "e6q9204                                2.0   \n",
-       "e5modd7                                4.0   \n",
-       "e5xhbyd                                2.0   \n",
-       "e5oaf7h                                2.0   \n",
-       "e6nir3u                                1.0   \n",
-       "e6c3xdn                                2.0   \n",
-       "e5d3zaa                                2.0   \n",
-       "e5gnjv9                                8.0   \n",
-       "e69gw2t                                2.0   \n",
-       "e5syrih                                3.0   \n",
-       "e5sa2yf                                1.0   \n",
-       "e6ai7z5                                3.0   \n",
-       "...                                    ...   \n",
-       "e5smhzk                                2.0   \n",
-       "e5v91s0                                5.0   \n",
-       "e6n6di6                                3.0   \n",
-       "e6iqq30                                6.0   \n",
-       "e5bfad7                                3.0   \n",
-       "e6x5he5                                4.0   \n",
-       "e6l9uyf                                5.0   \n",
-       "e57hyr1                                4.0   \n",
-       "e5b8sj7                                3.0   \n",
-       "e6nlep7                                9.0   \n",
-       "e6ltazd                                4.0   \n",
-       "e57a6qq                                2.0   \n",
-       "e5qc7eb                                3.0   \n",
-       "e6hqt5y                                4.0   \n",
-       "e5ua84v                                3.0   \n",
-       "e65m7kq                                4.0   \n",
-       "e5ggtru                                4.0   \n",
-       "e5pmmig                                2.0   \n",
-       "e64l6vq                                3.0   \n",
-       "e6fjx0d                                2.0   \n",
-       "e5h3xyy                                4.0   \n",
-       "e589ri5                                6.0   \n",
-       "e5beuqa                                3.0   \n",
-       "e5lqoj1                                5.0   \n",
-       "e5kvch1                                3.0   \n",
-       "e6srvwm                                3.0   \n",
-       "e5o65mk                                1.0   \n",
-       "e647cm8                                4.0   \n",
-       "e58n526                                9.0   \n",
-       "e69r2kg                                2.0   \n",
-       "\n",
-       "         max[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.0   \n",
-       "e5ywqyk                                           2.0   \n",
-       "e5qv9rj                                           3.0   \n",
-       "e6jhojf                                           2.0   \n",
-       "e6989ii                                           2.0   \n",
-       "e69lgse                                           3.0   \n",
-       "e5kwkg2                                           2.0   \n",
-       "e6mehe7                                           2.0   \n",
-       "e6m0hsd                                           2.0   \n",
-       "e64r385                                           2.0   \n",
-       "e5surbt                                           1.0   \n",
-       "e58gxii                                           2.0   \n",
-       "e64vc8y                                           1.0   \n",
-       "e57504g                                           2.0   \n",
-       "e5borjq                                           3.0   \n",
-       "e64n9zv                                           2.0   \n",
-       "e582ud3                                           2.0   \n",
-       "e64i9cf                                           2.0   \n",
-       "e6q9204                                           2.0   \n",
-       "e5modd7                                           4.0   \n",
-       "e5xhbyd                                           2.0   \n",
-       "e5oaf7h                                           2.0   \n",
-       "e6nir3u                                           2.0   \n",
-       "e6c3xdn                                           2.0   \n",
-       "e5d3zaa                                           2.0   \n",
-       "e5gnjv9                                           1.0   \n",
-       "e69gw2t                                           2.0   \n",
-       "e5syrih                                           3.0   \n",
-       "e5sa2yf                                           1.0   \n",
-       "e6ai7z5                                           1.0   \n",
-       "...                                               ...   \n",
-       "e5smhzk                                           1.0   \n",
-       "e5v91s0                                           2.0   \n",
-       "e6n6di6                                           3.0   \n",
-       "e6iqq30                                           1.0   \n",
-       "e5bfad7                                           2.0   \n",
-       "e6x5he5                                           2.0   \n",
-       "e6l9uyf                                           2.0   \n",
-       "e57hyr1                                           2.0   \n",
-       "e5b8sj7                                           3.0   \n",
-       "e6nlep7                                           0.0   \n",
-       "e6ltazd                                           4.0   \n",
-       "e57a6qq                                           2.0   \n",
-       "e5qc7eb                                           3.0   \n",
-       "e6hqt5y                                           4.0   \n",
-       "e5ua84v                                           3.0   \n",
-       "e65m7kq                                           2.0   \n",
-       "e5ggtru                                           4.0   \n",
-       "e5pmmig                                           2.0   \n",
-       "e64l6vq                                           2.0   \n",
-       "e6fjx0d                                           1.0   \n",
-       "e5h3xyy                                           2.0   \n",
-       "e589ri5                                           1.0   \n",
-       "e5beuqa                                           3.0   \n",
-       "e5lqoj1                                           1.0   \n",
-       "e5kvch1                                           1.0   \n",
-       "e6srvwm                                           2.0   \n",
-       "e5o65mk                                           1.0   \n",
-       "e647cm8                                           3.0   \n",
-       "e58n526                                           0.0   \n",
-       "e69r2kg                                           2.0   \n",
+       "         prop-nonzero[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.666667       \n",
+       "e5ytz1d                                           0.333333       \n",
+       "e6ls80j                                           0.333333       \n",
+       "e5mhgl5                                           0.666667       \n",
+       "e6w6fah                                           0.000000       \n",
+       "...                                                    ...       \n",
+       "e65ca8k                                           0.777778       \n",
+       "e6cdkpy                                           0.333333       \n",
+       "e5wc4tj                                           0.888889       \n",
+       "e6ua0sb                                           0.444444       \n",
+       "e5ua84v                                           0.555556       \n",
        "\n",
-       "         max[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                3.0   \n",
-       "e5ywqyk                                2.0   \n",
-       "e5qv9rj                                3.0   \n",
-       "e6jhojf                                2.0   \n",
-       "e6989ii                                2.0   \n",
-       "e69lgse                                3.0   \n",
-       "e5kwkg2                                3.0   \n",
-       "e6mehe7                                3.0   \n",
-       "e6m0hsd                                2.0   \n",
-       "e64r385                                2.0   \n",
-       "e5surbt                                5.0   \n",
-       "e58gxii                                2.0   \n",
-       "e64vc8y                                6.0   \n",
-       "e57504g                                2.0   \n",
-       "e5borjq                                3.0   \n",
-       "e64n9zv                                2.0   \n",
-       "e582ud3                                6.0   \n",
-       "e64i9cf                                4.0   \n",
-       "e6q9204                                2.0   \n",
-       "e5modd7                                4.0   \n",
-       "e5xhbyd                                2.0   \n",
-       "e5oaf7h                                2.0   \n",
-       "e6nir3u                                2.0   \n",
-       "e6c3xdn                                2.0   \n",
-       "e5d3zaa                                2.0   \n",
-       "e5gnjv9                                8.0   \n",
-       "e69gw2t                                2.0   \n",
-       "e5syrih                                3.0   \n",
-       "e5sa2yf                                1.0   \n",
-       "e6ai7z5                                3.0   \n",
-       "...                                    ...   \n",
-       "e5smhzk                                2.0   \n",
-       "e5v91s0                                5.0   \n",
-       "e6n6di6                                3.0   \n",
-       "e6iqq30                                6.0   \n",
-       "e5bfad7                                3.0   \n",
-       "e6x5he5                                4.0   \n",
-       "e6l9uyf                                5.0   \n",
-       "e57hyr1                                4.0   \n",
-       "e5b8sj7                                3.0   \n",
-       "e6nlep7                                9.0   \n",
-       "e6ltazd                                4.0   \n",
-       "e57a6qq                                2.0   \n",
-       "e5qc7eb                                3.0   \n",
-       "e6hqt5y                                4.0   \n",
-       "e5ua84v                                3.0   \n",
-       "e65m7kq                                4.0   \n",
-       "e5ggtru                                4.0   \n",
-       "e5pmmig                                2.0   \n",
-       "e64l6vq                                3.0   \n",
-       "e6fjx0d                                2.0   \n",
-       "e5h3xyy                                4.0   \n",
-       "e589ri5                                6.0   \n",
-       "e5beuqa                                3.0   \n",
-       "e5lqoj1                                5.0   \n",
-       "e5kvch1                                3.0   \n",
-       "e6srvwm                                3.0   \n",
-       "e5o65mk                                2.0   \n",
-       "e647cm8                                4.0   \n",
-       "e58n526                                9.0   \n",
-       "e69r2kg                                2.0   \n",
+       "         prop-multiple[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.166667        \n",
+       "e5ytz1d                                           0.666667        \n",
+       "e6ls80j                                           0.333333        \n",
+       "e5mhgl5                                           0.333333        \n",
+       "e6w6fah                                           0.000000        \n",
+       "...                                                    ...        \n",
+       "e65ca8k                                           0.000000        \n",
+       "e6cdkpy                                           0.666667        \n",
+       "e5wc4tj                                           0.000000        \n",
+       "e6ua0sb                                           0.250000        \n",
+       "e5ua84v                                           0.400000        \n",
        "\n",
-       "         max[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                            3.0   \n",
-       "e5ywqyk                                            2.0   \n",
-       "e5qv9rj                                            1.0   \n",
-       "e6jhojf                                            4.0   \n",
-       "e6989ii                                            1.0   \n",
-       "e69lgse                                            2.0   \n",
-       "e5kwkg2                                            1.0   \n",
-       "e6mehe7                                            3.0   \n",
-       "e6m0hsd                                            2.0   \n",
-       "e64r385                                            2.0   \n",
-       "e5surbt                                            1.0   \n",
-       "e58gxii                                            3.0   \n",
-       "e64vc8y                                            1.0   \n",
-       "e57504g                                            2.0   \n",
-       "e5borjq                                            1.0   \n",
-       "e64n9zv                                            2.0   \n",
-       "e582ud3                                            1.0   \n",
-       "e64i9cf                                            2.0   \n",
-       "e6q9204                                            2.0   \n",
-       "e5modd7                                            1.0   \n",
-       "e5xhbyd                                            2.0   \n",
-       "e5oaf7h                                            2.0   \n",
-       "e6nir3u                                            1.0   \n",
-       "e6c3xdn                                            1.0   \n",
-       "e5d3zaa                                            1.0   \n",
-       "e5gnjv9                                            1.0   \n",
-       "e69gw2t                                            2.0   \n",
-       "e5syrih                                            2.0   \n",
-       "e5sa2yf                                            1.0   \n",
-       "e6ai7z5                                            4.0   \n",
-       "...                                                ...   \n",
-       "e5smhzk                                            2.0   \n",
-       "e5v91s0                                            1.0   \n",
-       "e6n6di6                                            2.0   \n",
-       "e6iqq30                                            1.0   \n",
-       "e5bfad7                                            2.0   \n",
-       "e6x5he5                                            4.0   \n",
-       "e6l9uyf                                            1.0   \n",
-       "e57hyr1                                            1.0   \n",
-       "e5b8sj7                                            1.0   \n",
-       "e6nlep7                                            0.0   \n",
-       "e6ltazd                                            1.0   \n",
-       "e57a6qq                                            2.0   \n",
-       "e5qc7eb                                            1.0   \n",
-       "e6hqt5y                                            1.0   \n",
-       "e5ua84v                                            2.0   \n",
-       "e65m7kq                                            1.0   \n",
-       "e5ggtru                                            1.0   \n",
-       "e5pmmig                                            2.0   \n",
-       "e64l6vq                                            2.0   \n",
-       "e6fjx0d                                            1.0   \n",
-       "e5h3xyy                                            1.0   \n",
-       "e589ri5                                            1.0   \n",
-       "e5beuqa                                            3.0   \n",
-       "e5lqoj1                                            2.0   \n",
-       "e5kvch1                                            1.0   \n",
-       "e6srvwm                                            1.0   \n",
-       "e5o65mk                                            1.0   \n",
-       "e647cm8                                            1.0   \n",
-       "e58n526                                            0.0   \n",
-       "e69r2kg                                            2.0   \n",
+       "         entropy[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                          1.667462   \n",
+       "e5ytz1d                                          1.011404   \n",
+       "e6ls80j                                          0.950271   \n",
+       "e5mhgl5                                          1.732868   \n",
+       "e6w6fah                                               NaN   \n",
+       "...                                                   ...   \n",
+       "e65ca8k                                          1.945910   \n",
+       "e6cdkpy                                          1.054920   \n",
+       "e5wc4tj                                          2.079442   \n",
+       "e6ua0sb                                          1.153742   \n",
+       "e5ua84v                                          1.494175   \n",
        "\n",
-       "         max[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                 3.0   \n",
-       "e5ywqyk                                 2.0   \n",
-       "e5qv9rj                                 1.0   \n",
-       "e6jhojf                                 4.0   \n",
-       "e6989ii                                 1.0   \n",
-       "e69lgse                                 2.0   \n",
-       "e5kwkg2                                 1.0   \n",
-       "e6mehe7                                 3.0   \n",
-       "e6m0hsd                                 2.0   \n",
-       "e64r385                                 2.0   \n",
-       "e5surbt                                 1.0   \n",
-       "e58gxii                                 3.0   \n",
-       "e64vc8y                                 1.0   \n",
-       "e57504g                                 2.0   \n",
-       "e5borjq                                 2.0   \n",
-       "e64n9zv                                 2.0   \n",
-       "e582ud3                                 1.0   \n",
-       "e64i9cf                                 2.0   \n",
-       "e6q9204                                 3.0   \n",
-       "e5modd7                                 1.0   \n",
-       "e5xhbyd                                 2.0   \n",
-       "e5oaf7h                                 2.0   \n",
-       "e6nir3u                                 1.0   \n",
-       "e6c3xdn                                 1.0   \n",
-       "e5d3zaa                                 2.0   \n",
-       "e5gnjv9                                 2.0   \n",
-       "e69gw2t                                 2.0   \n",
-       "e5syrih                                 2.0   \n",
-       "e5sa2yf                                 1.0   \n",
-       "e6ai7z5                                 4.0   \n",
-       "...                                     ...   \n",
-       "e5smhzk                                 2.0   \n",
-       "e5v91s0                                 1.0   \n",
-       "e6n6di6                                 2.0   \n",
-       "e6iqq30                                 1.0   \n",
-       "e5bfad7                                 2.0   \n",
-       "e6x5he5                                 4.0   \n",
-       "e6l9uyf                                 2.0   \n",
-       "e57hyr1                                 2.0   \n",
-       "e5b8sj7                                 2.0   \n",
-       "e6nlep7                                 1.0   \n",
-       "e6ltazd                                 2.0   \n",
-       "e57a6qq                                 2.0   \n",
-       "e5qc7eb                                 2.0   \n",
-       "e6hqt5y                                 2.0   \n",
-       "e5ua84v                                 3.0   \n",
-       "e65m7kq                                 2.0   \n",
-       "e5ggtru                                 2.0   \n",
-       "e5pmmig                                 3.0   \n",
-       "e64l6vq                                 2.0   \n",
-       "e6fjx0d                                 2.0   \n",
-       "e5h3xyy                                 2.0   \n",
-       "e589ri5                                 1.0   \n",
-       "e5beuqa                                 4.0   \n",
-       "e5lqoj1                                 3.0   \n",
-       "e5kvch1                                 2.0   \n",
-       "e6srvwm                                 2.0   \n",
-       "e5o65mk                                 1.0   \n",
-       "e647cm8                                 1.0   \n",
-       "e58n526                                 1.0   \n",
-       "e69r2kg                                 2.0   \n",
+       "         2nd-largest / max[indegree over c->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.333333            \n",
+       "e5ytz1d                                           0.666667            \n",
+       "e6ls80j                                           0.333333            \n",
+       "e5mhgl5                                           1.000000            \n",
+       "e6w6fah                                                NaN            \n",
+       "...                                                    ...            \n",
+       "e65ca8k                                           1.000000            \n",
+       "e6cdkpy                                           1.000000            \n",
+       "e5wc4tj                                           1.000000            \n",
+       "e6ua0sb                                           0.250000            \n",
+       "e5ua84v                                           0.666667            \n",
        "\n",
        "         max[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                            3.0   \n",
-       "e5ywqyk                                            4.0   \n",
-       "e5qv9rj                                            1.0   \n",
-       "e6jhojf                                            4.0   \n",
-       "e6989ii                                            4.0   \n",
-       "e69lgse                                            2.0   \n",
-       "e5kwkg2                                            1.0   \n",
-       "e6mehe7                                            3.0   \n",
-       "e6m0hsd                                            4.0   \n",
-       "e64r385                                            2.0   \n",
-       "e5surbt                                            1.0   \n",
-       "e58gxii                                            3.0   \n",
-       "e64vc8y                                            1.0   \n",
-       "e57504g                                            2.0   \n",
-       "e5borjq                                            1.0   \n",
-       "e64n9zv                                            3.0   \n",
-       "e582ud3                                            1.0   \n",
-       "e64i9cf                                            3.0   \n",
-       "e6q9204                                            3.0   \n",
-       "e5modd7                                            1.0   \n",
-       "e5xhbyd                                            3.0   \n",
-       "e5oaf7h                                            4.0   \n",
-       "e6nir3u                                            4.0   \n",
-       "e6c3xdn                                            1.0   \n",
-       "e5d3zaa                                            2.0   \n",
-       "e5gnjv9                                            1.0   \n",
-       "e69gw2t                                            3.0   \n",
-       "e5syrih                                            2.0   \n",
-       "e5sa2yf                                            4.0   \n",
-       "e6ai7z5                                            4.0   \n",
+       "e5hm9mp                                            2.0   \n",
+       "e5ytz1d                                            1.0   \n",
+       "e6ls80j                                            2.0   \n",
+       "e5mhgl5                                            2.0   \n",
+       "e6w6fah                                            0.0   \n",
        "...                                                ...   \n",
-       "e5smhzk                                            4.0   \n",
-       "e5v91s0                                            1.0   \n",
-       "e6n6di6                                            2.0   \n",
-       "e6iqq30                                            1.0   \n",
-       "e5bfad7                                            2.0   \n",
-       "e6x5he5                                            4.0   \n",
-       "e6l9uyf                                            1.0   \n",
-       "e57hyr1                                            1.0   \n",
-       "e5b8sj7                                            1.0   \n",
-       "e6nlep7                                            0.0   \n",
-       "e6ltazd                                            3.0   \n",
-       "e57a6qq                                            3.0   \n",
-       "e5qc7eb                                            2.0   \n",
-       "e6hqt5y                                            1.0   \n",
+       "e65ca8k                                            7.0   \n",
+       "e6cdkpy                                            1.0   \n",
+       "e5wc4tj                                            4.0   \n",
+       "e6ua0sb                                            2.0   \n",
        "e5ua84v                                            2.0   \n",
-       "e65m7kq                                            1.0   \n",
-       "e5ggtru                                            1.0   \n",
-       "e5pmmig                                            3.0   \n",
-       "e64l6vq                                            3.0   \n",
-       "e6fjx0d                                            4.0   \n",
-       "e5h3xyy                                            1.0   \n",
-       "e589ri5                                            1.0   \n",
-       "e5beuqa                                            3.0   \n",
-       "e5lqoj1                                            2.0   \n",
-       "e5kvch1                                            2.0   \n",
-       "e6srvwm                                            1.0   \n",
-       "e5o65mk                                            4.0   \n",
-       "e647cm8                                            1.0   \n",
-       "e58n526                                            0.0   \n",
-       "e69r2kg                                            2.0   \n",
        "\n",
-       "         max[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                 3.0   \n",
-       "e5ywqyk                                 4.0   \n",
-       "e5qv9rj                                 1.0   \n",
-       "e6jhojf                                 4.0   \n",
-       "e6989ii                                 4.0   \n",
-       "e69lgse                                 2.0   \n",
-       "e5kwkg2                                 1.0   \n",
-       "e6mehe7                                 3.0   \n",
-       "e6m0hsd                                 5.0   \n",
-       "e64r385                                 2.0   \n",
-       "e5surbt                                 1.0   \n",
-       "e58gxii                                 3.0   \n",
-       "e64vc8y                                 1.0   \n",
-       "e57504g                                 2.0   \n",
-       "e5borjq                                 2.0   \n",
-       "e64n9zv                                 4.0   \n",
-       "e582ud3                                 1.0   \n",
-       "e64i9cf                                 3.0   \n",
-       "e6q9204                                 4.0   \n",
-       "e5modd7                                 1.0   \n",
-       "e5xhbyd                                 3.0   \n",
-       "e5oaf7h                                 5.0   \n",
-       "e6nir3u                                 4.0   \n",
-       "e6c3xdn                                 1.0   \n",
-       "e5d3zaa                                 3.0   \n",
-       "e5gnjv9                                 2.0   \n",
-       "e69gw2t                                 3.0   \n",
-       "e5syrih                                 2.0   \n",
-       "e5sa2yf                                 5.0   \n",
-       "e6ai7z5                                 5.0   \n",
-       "...                                     ...   \n",
-       "e5smhzk                                 4.0   \n",
-       "e5v91s0                                 1.0   \n",
-       "e6n6di6                                 2.0   \n",
-       "e6iqq30                                 1.0   \n",
-       "e5bfad7                                 2.0   \n",
-       "e6x5he5                                 4.0   \n",
-       "e6l9uyf                                 2.0   \n",
-       "e57hyr1                                 2.0   \n",
-       "e5b8sj7                                 2.0   \n",
-       "e6nlep7                                 1.0   \n",
-       "e6ltazd                                 3.0   \n",
-       "e57a6qq                                 3.0   \n",
-       "e5qc7eb                                 2.0   \n",
-       "e6hqt5y                                 2.0   \n",
-       "e5ua84v                                 3.0   \n",
-       "e65m7kq                                 2.0   \n",
-       "e5ggtru                                 2.0   \n",
-       "e5pmmig                                 3.0   \n",
-       "e64l6vq                                 3.0   \n",
-       "e6fjx0d                                 4.0   \n",
-       "e5h3xyy                                 2.0   \n",
-       "e589ri5                                 1.0   \n",
-       "e5beuqa                                 4.0   \n",
-       "e5lqoj1                                 3.0   \n",
-       "e5kvch1                                 2.0   \n",
-       "e6srvwm                                 2.0   \n",
-       "e5o65mk                                 4.0   \n",
-       "e647cm8                                 1.0   \n",
-       "e58n526                                 1.0   \n",
-       "e69r2kg                                 2.0   \n",
+       "         max[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           3.0   \n",
+       "e5ytz1d                                           3.0   \n",
+       "e6ls80j                                           3.0   \n",
+       "e5mhgl5                                           2.0   \n",
+       "e6w6fah                                           0.0   \n",
+       "...                                               ...   \n",
+       "e65ca8k                                           1.0   \n",
+       "e6cdkpy                                           2.0   \n",
+       "e5wc4tj                                           1.0   \n",
+       "e6ua0sb                                           4.0   \n",
+       "e5ua84v                                           3.0   \n",
        "\n",
-       "         mean-nonzero[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.500000       \n",
-       "e5ywqyk                                           1.333333       \n",
-       "e5qv9rj                                           1.500000       \n",
-       "e6jhojf                                           1.400000       \n",
-       "e6989ii                                           1.000000       \n",
-       "e69lgse                                           1.500000       \n",
-       "e5kwkg2                                           1.200000       \n",
-       "e6mehe7                                           1.250000       \n",
-       "e6m0hsd                                           1.333333       \n",
-       "e64r385                                           1.400000       \n",
-       "e5surbt                                           1.000000       \n",
-       "e58gxii                                           1.750000       \n",
-       "e64vc8y                                           1.000000       \n",
-       "e57504g                                           1.400000       \n",
-       "e5borjq                                           1.750000       \n",
-       "e64n9zv                                           1.333333       \n",
-       "e582ud3                                           1.500000       \n",
-       "e64i9cf                                           1.333333       \n",
-       "e6q9204                                           2.000000       \n",
-       "e5modd7                                           2.666667       \n",
-       "e5xhbyd                                           1.500000       \n",
-       "e5oaf7h                                           2.000000       \n",
-       "e6nir3u                                           1.000000       \n",
-       "e6c3xdn                                           1.142857       \n",
-       "e5d3zaa                                           1.666667       \n",
-       "e5gnjv9                                           1.000000       \n",
-       "e69gw2t                                           1.666667       \n",
-       "e5syrih                                           2.666667       \n",
-       "e5sa2yf                                           1.000000       \n",
-       "e6ai7z5                                           1.200000       \n",
-       "...                                                    ...       \n",
-       "e5smhzk                                           1.000000       \n",
-       "e5v91s0                                           1.333333       \n",
-       "e6n6di6                                           2.000000       \n",
-       "e6iqq30                                           1.000000       \n",
-       "e5bfad7                                           1.500000       \n",
-       "e6x5he5                                           1.000000       \n",
-       "e6l9uyf                                           1.333333       \n",
-       "e57hyr1                                           1.250000       \n",
-       "e5b8sj7                                           3.000000       \n",
-       "e6nlep7                                           0.000000       \n",
-       "e6ltazd                                           2.500000       \n",
-       "e57a6qq                                           2.000000       \n",
-       "e5qc7eb                                           2.000000       \n",
-       "e6hqt5y                                           2.500000       \n",
-       "e5ua84v                                           2.000000       \n",
-       "e65m7kq                                           1.666667       \n",
-       "e5ggtru                                           2.666667       \n",
-       "e5pmmig                                           1.500000       \n",
-       "e64l6vq                                           1.250000       \n",
-       "e6fjx0d                                           1.000000       \n",
-       "e5h3xyy                                           1.250000       \n",
-       "e589ri5                                           1.000000       \n",
-       "e5beuqa                                           1.750000       \n",
-       "e5lqoj1                                           1.000000       \n",
-       "e5kvch1                                           1.250000       \n",
-       "e6srvwm                                           1.500000       \n",
-       "e5o65mk                                           1.000000       \n",
-       "e647cm8                                           1.666667       \n",
-       "e58n526                                           0.000000       \n",
-       "e69r2kg                                           1.750000       \n",
+       "         argmax[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                               1.0   \n",
+       "e5ytz1d                                               3.0   \n",
+       "e6ls80j                                               2.0   \n",
+       "e5mhgl5                                               3.0   \n",
+       "e6w6fah                                               0.0   \n",
+       "...                                                   ...   \n",
+       "e65ca8k                                               1.0   \n",
+       "e6cdkpy                                               2.0   \n",
+       "e5wc4tj                                               0.0   \n",
+       "e6ua0sb                                               2.0   \n",
+       "e5ua84v                                               0.0   \n",
        "\n",
-       "         mean-nonzero[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                    2.000000   \n",
-       "e5ywqyk                                    1.666667   \n",
-       "e5qv9rj                                    1.800000   \n",
-       "e6jhojf                                    1.600000   \n",
-       "e6989ii                                    1.000000   \n",
-       "e69lgse                                    2.000000   \n",
-       "e5kwkg2                                    1.500000   \n",
-       "e6mehe7                                    2.000000   \n",
-       "e6m0hsd                                    1.333333   \n",
-       "e64r385                                    1.500000   \n",
-       "e5surbt                                    1.800000   \n",
-       "e58gxii                                    2.000000   \n",
-       "e64vc8y                                    2.250000   \n",
-       "e57504g                                    1.500000   \n",
-       "e5borjq                                    1.800000   \n",
-       "e64n9zv                                    1.333333   \n",
-       "e582ud3                                    3.000000   \n",
-       "e64i9cf                                    2.333333   \n",
-       "e6q9204                                    1.750000   \n",
-       "e5modd7                                    2.250000   \n",
-       "e5xhbyd                                    1.500000   \n",
-       "e5oaf7h                                    2.000000   \n",
-       "e6nir3u                                    1.000000   \n",
-       "e6c3xdn                                    1.125000   \n",
-       "e5d3zaa                                    1.750000   \n",
-       "e5gnjv9                                    4.500000   \n",
-       "e69gw2t                                    1.750000   \n",
-       "e5syrih                                    2.250000   \n",
-       "e5sa2yf                                    1.000000   \n",
-       "e6ai7z5                                    1.600000   \n",
-       "...                                             ...   \n",
-       "e5smhzk                                    1.333333   \n",
-       "e5v91s0                                    2.250000   \n",
-       "e6n6di6                                    1.800000   \n",
-       "e6iqq30                                    2.250000   \n",
-       "e5bfad7                                    2.250000   \n",
-       "e6x5he5                                    1.600000   \n",
-       "e6l9uyf                                    2.250000   \n",
-       "e57hyr1                                    1.800000   \n",
-       "e5b8sj7                                    3.000000   \n",
-       "e6nlep7                                    9.000000   \n",
-       "e6ltazd                                    2.000000   \n",
-       "e57a6qq                                    2.000000   \n",
-       "e5qc7eb                                    2.333333   \n",
-       "e6hqt5y                                    3.000000   \n",
-       "e5ua84v                                    1.800000   \n",
-       "e65m7kq                                    2.250000   \n",
-       "e5ggtru                                    2.250000   \n",
-       "e5pmmig                                    1.400000   \n",
-       "e64l6vq                                    1.750000   \n",
-       "e6fjx0d                                    1.333333   \n",
-       "e5h3xyy                                    1.800000   \n",
-       "e589ri5                                    2.250000   \n",
-       "e5beuqa                                    1.800000   \n",
-       "e5lqoj1                                    2.000000   \n",
-       "e5kvch1                                    1.600000   \n",
-       "e6srvwm                                    1.800000   \n",
-       "e5o65mk                                    1.000000   \n",
-       "e647cm8                                    2.250000   \n",
-       "e58n526                                    9.000000   \n",
-       "e69r2kg                                    1.800000   \n",
+       "         argmax[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                              0.0   \n",
+       "e5ytz1d                                              1.0   \n",
+       "e6ls80j                                              1.0   \n",
+       "e5mhgl5                                              0.0   \n",
+       "e6w6fah                                              0.0   \n",
+       "...                                                  ...   \n",
+       "e65ca8k                                              1.0   \n",
+       "e6cdkpy                                              0.0   \n",
+       "e5wc4tj                                              0.0   \n",
+       "e6ua0sb                                              1.0   \n",
+       "e5ua84v                                              0.0   \n",
        "\n",
-       "         mean-nonzero[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.000000       \n",
-       "e5ywqyk                                           1.142857       \n",
-       "e5qv9rj                                           1.500000       \n",
-       "e6jhojf                                           1.142857       \n",
-       "e6989ii                                           1.000000       \n",
-       "e69lgse                                           1.500000       \n",
-       "e5kwkg2                                           1.200000       \n",
-       "e6mehe7                                           1.200000       \n",
-       "e6m0hsd                                           1.142857       \n",
-       "e64r385                                           1.400000       \n",
-       "e5surbt                                           1.000000       \n",
-       "e58gxii                                           1.400000       \n",
-       "e64vc8y                                           1.000000       \n",
-       "e57504g                                           1.400000       \n",
-       "e5borjq                                           1.750000       \n",
-       "e64n9zv                                           1.142857       \n",
-       "e582ud3                                           1.500000       \n",
-       "e64i9cf                                           1.250000       \n",
-       "e6q9204                                           1.333333       \n",
-       "e5modd7                                           2.666667       \n",
-       "e5xhbyd                                           1.333333       \n",
-       "e5oaf7h                                           1.333333       \n",
-       "e6nir3u                                           1.000000       \n",
-       "e6c3xdn                                           1.142857       \n",
-       "e5d3zaa                                           1.400000       \n",
-       "e5gnjv9                                           1.000000       \n",
-       "e69gw2t                                           1.400000       \n",
-       "e5syrih                                           1.600000       \n",
-       "e5sa2yf                                           1.000000       \n",
-       "e6ai7z5                                           1.000000       \n",
-       "...                                                    ...       \n",
-       "e5smhzk                                           1.000000       \n",
-       "e5v91s0                                           1.333333       \n",
-       "e6n6di6                                           1.600000       \n",
-       "e6iqq30                                           1.000000       \n",
-       "e5bfad7                                           1.500000       \n",
-       "e6x5he5                                           1.000000       \n",
-       "e6l9uyf                                           1.333333       \n",
-       "e57hyr1                                           1.250000       \n",
-       "e5b8sj7                                           2.000000       \n",
-       "e6nlep7                                           0.000000       \n",
-       "e6ltazd                                           1.600000       \n",
-       "e57a6qq                                           1.333333       \n",
-       "e5qc7eb                                           1.750000       \n",
-       "e6hqt5y                                           2.500000       \n",
-       "e5ua84v                                           1.600000       \n",
-       "e65m7kq                                           1.250000       \n",
-       "e5ggtru                                           2.000000       \n",
-       "e5pmmig                                           1.142857       \n",
-       "e64l6vq                                           1.200000       \n",
-       "e6fjx0d                                           1.000000       \n",
-       "e5h3xyy                                           1.250000       \n",
-       "e589ri5                                           1.000000       \n",
-       "e5beuqa                                           1.400000       \n",
-       "e5lqoj1                                           1.000000       \n",
-       "e5kvch1                                           1.000000       \n",
-       "e6srvwm                                           1.500000       \n",
-       "e5o65mk                                           1.000000       \n",
-       "e647cm8                                           1.666667       \n",
-       "e58n526                                           0.000000       \n",
-       "e69r2kg                                           1.400000       \n",
+       "         norm.max[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.250000    \n",
+       "e5ytz1d                                           0.166667    \n",
+       "e6ls80j                                           0.400000    \n",
+       "e5mhgl5                                           0.250000    \n",
+       "e6w6fah                                           0.000000    \n",
+       "...                                                    ...    \n",
+       "e65ca8k                                           1.000000    \n",
+       "e6cdkpy                                           0.200000    \n",
+       "e5wc4tj                                           0.500000    \n",
+       "e6ua0sb                                           0.285714    \n",
+       "e5ua84v                                           0.250000    \n",
        "\n",
-       "         mean-nonzero[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                    1.285714   \n",
-       "e5ywqyk                                    1.125000   \n",
-       "e5qv9rj                                    1.800000   \n",
-       "e6jhojf                                    1.125000   \n",
-       "e6989ii                                    1.000000   \n",
-       "e69lgse                                    1.800000   \n",
-       "e5kwkg2                                    1.500000   \n",
-       "e6mehe7                                    1.500000   \n",
-       "e6m0hsd                                    1.125000   \n",
-       "e64r385                                    1.500000   \n",
-       "e5surbt                                    1.800000   \n",
-       "e58gxii                                    1.500000   \n",
-       "e64vc8y                                    2.250000   \n",
-       "e57504g                                    1.500000   \n",
-       "e5borjq                                    1.800000   \n",
-       "e64n9zv                                    1.125000   \n",
-       "e582ud3                                    3.000000   \n",
-       "e64i9cf                                    1.800000   \n",
-       "e6q9204                                    1.285714   \n",
-       "e5modd7                                    2.250000   \n",
-       "e5xhbyd                                    1.285714   \n",
-       "e5oaf7h                                    1.285714   \n",
-       "e6nir3u                                    1.000000   \n",
-       "e6c3xdn                                    1.125000   \n",
-       "e5d3zaa                                    1.500000   \n",
-       "e5gnjv9                                    4.500000   \n",
-       "e69gw2t                                    1.500000   \n",
-       "e5syrih                                    1.500000   \n",
-       "e5sa2yf                                    1.000000   \n",
-       "e6ai7z5                                    1.285714   \n",
-       "...                                             ...   \n",
-       "e5smhzk                                    1.125000   \n",
-       "e5v91s0                                    2.250000   \n",
-       "e6n6di6                                    1.500000   \n",
-       "e6iqq30                                    2.250000   \n",
-       "e5bfad7                                    1.800000   \n",
-       "e6x5he5                                    1.600000   \n",
-       "e6l9uyf                                    2.250000   \n",
-       "e57hyr1                                    1.800000   \n",
-       "e5b8sj7                                    2.250000   \n",
-       "e6nlep7                                    9.000000   \n",
-       "e6ltazd                                    1.500000   \n",
-       "e57a6qq                                    1.285714   \n",
-       "e5qc7eb                                    1.800000   \n",
-       "e6hqt5y                                    3.000000   \n",
-       "e5ua84v                                    1.500000   \n",
-       "e65m7kq                                    1.800000   \n",
-       "e5ggtru                                    1.800000   \n",
-       "e5pmmig                                    1.125000   \n",
-       "e64l6vq                                    1.500000   \n",
-       "e6fjx0d                                    1.125000   \n",
-       "e5h3xyy                                    1.800000   \n",
-       "e589ri5                                    2.250000   \n",
-       "e5beuqa                                    1.500000   \n",
-       "e5lqoj1                                    1.800000   \n",
-       "e5kvch1                                    1.285714   \n",
-       "e6srvwm                                    1.800000   \n",
-       "e5o65mk                                    1.000000   \n",
-       "e647cm8                                    2.250000   \n",
-       "e58n526                                    9.000000   \n",
-       "e69r2kg                                    1.500000   \n",
+       "         norm.max[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.375000   \n",
+       "e5ytz1d                                           0.500000   \n",
+       "e6ls80j                                           0.600000   \n",
+       "e5mhgl5                                           0.250000   \n",
+       "e6w6fah                                           0.000000   \n",
+       "...                                                    ...   \n",
+       "e65ca8k                                           0.142857   \n",
+       "e6cdkpy                                           0.400000   \n",
+       "e5wc4tj                                           0.125000   \n",
+       "e6ua0sb                                           0.571429   \n",
+       "e5ua84v                                           0.375000   \n",
        "\n",
-       "         mean-nonzero[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.000000       \n",
-       "e5ywqyk                                           1.142857       \n",
-       "e5qv9rj                                           1.500000       \n",
-       "e6jhojf                                           1.142857       \n",
-       "e6989ii                                           1.142857       \n",
-       "e69lgse                                           1.500000       \n",
-       "e5kwkg2                                           1.200000       \n",
-       "e6mehe7                                           1.200000       \n",
-       "e6m0hsd                                           1.142857       \n",
-       "e64r385                                           1.400000       \n",
-       "e5surbt                                           1.000000       \n",
-       "e58gxii                                           1.400000       \n",
-       "e64vc8y                                           1.000000       \n",
-       "e57504g                                           1.400000       \n",
-       "e5borjq                                           1.750000       \n",
-       "e64n9zv                                           1.142857       \n",
-       "e582ud3                                           1.500000       \n",
-       "e64i9cf                                           1.250000       \n",
-       "e6q9204                                           1.333333       \n",
-       "e5modd7                                           2.666667       \n",
-       "e5xhbyd                                           1.333333       \n",
-       "e5oaf7h                                           1.333333       \n",
-       "e6nir3u                                           1.142857       \n",
-       "e6c3xdn                                           1.142857       \n",
-       "e5d3zaa                                           1.400000       \n",
-       "e5gnjv9                                           1.000000       \n",
-       "e69gw2t                                           1.400000       \n",
-       "e5syrih                                           1.600000       \n",
-       "e5sa2yf                                           1.000000       \n",
-       "e6ai7z5                                           1.000000       \n",
+       "         2nd-largest[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                2.0       \n",
+       "e5ytz1d                                                1.0       \n",
+       "e6ls80j                                                1.0       \n",
+       "e5mhgl5                                                2.0       \n",
+       "e6w6fah                                                0.0       \n",
        "...                                                    ...       \n",
-       "e5smhzk                                           1.000000       \n",
-       "e5v91s0                                           1.333333       \n",
-       "e6n6di6                                           1.600000       \n",
-       "e6iqq30                                           1.000000       \n",
-       "e5bfad7                                           1.500000       \n",
-       "e6x5he5                                           1.250000       \n",
-       "e6l9uyf                                           1.333333       \n",
-       "e57hyr1                                           1.250000       \n",
-       "e5b8sj7                                           2.000000       \n",
-       "e6nlep7                                           0.000000       \n",
-       "e6ltazd                                           1.600000       \n",
-       "e57a6qq                                           1.333333       \n",
-       "e5qc7eb                                           1.750000       \n",
-       "e6hqt5y                                           2.500000       \n",
-       "e5ua84v                                           1.600000       \n",
-       "e65m7kq                                           1.250000       \n",
-       "e5ggtru                                           2.000000       \n",
-       "e5pmmig                                           1.142857       \n",
-       "e64l6vq                                           1.200000       \n",
-       "e6fjx0d                                           1.000000       \n",
-       "e5h3xyy                                           1.250000       \n",
-       "e589ri5                                           1.000000       \n",
-       "e5beuqa                                           1.400000       \n",
-       "e5lqoj1                                           1.000000       \n",
-       "e5kvch1                                           1.000000       \n",
-       "e6srvwm                                           1.500000       \n",
-       "e5o65mk                                           1.000000       \n",
-       "e647cm8                                           1.666667       \n",
-       "e58n526                                           0.000000       \n",
-       "e69r2kg                                           1.400000       \n",
-       "\n",
-       "         mean-nonzero[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                    1.285714   \n",
-       "e5ywqyk                                    1.125000   \n",
-       "e5qv9rj                                    1.800000   \n",
-       "e6jhojf                                    1.125000   \n",
-       "e6989ii                                    1.125000   \n",
-       "e69lgse                                    1.800000   \n",
-       "e5kwkg2                                    1.500000   \n",
-       "e6mehe7                                    1.500000   \n",
-       "e6m0hsd                                    1.125000   \n",
-       "e64r385                                    1.500000   \n",
-       "e5surbt                                    1.800000   \n",
-       "e58gxii                                    1.500000   \n",
-       "e64vc8y                                    2.250000   \n",
-       "e57504g                                    1.500000   \n",
-       "e5borjq                                    1.800000   \n",
-       "e64n9zv                                    1.125000   \n",
-       "e582ud3                                    3.000000   \n",
-       "e64i9cf                                    1.800000   \n",
-       "e6q9204                                    1.285714   \n",
-       "e5modd7                                    2.250000   \n",
-       "e5xhbyd                                    1.285714   \n",
-       "e5oaf7h                                    1.285714   \n",
-       "e6nir3u                                    1.125000   \n",
-       "e6c3xdn                                    1.125000   \n",
-       "e5d3zaa                                    1.500000   \n",
-       "e5gnjv9                                    4.500000   \n",
-       "e69gw2t                                    1.500000   \n",
-       "e5syrih                                    1.500000   \n",
-       "e5sa2yf                                    1.000000   \n",
-       "e6ai7z5                                    1.285714   \n",
-       "...                                             ...   \n",
-       "e5smhzk                                    1.125000   \n",
-       "e5v91s0                                    2.250000   \n",
-       "e6n6di6                                    1.500000   \n",
-       "e6iqq30                                    2.250000   \n",
-       "e5bfad7                                    1.800000   \n",
-       "e6x5he5                                    1.800000   \n",
-       "e6l9uyf                                    2.250000   \n",
-       "e57hyr1                                    1.800000   \n",
-       "e5b8sj7                                    2.250000   \n",
-       "e6nlep7                                    9.000000   \n",
-       "e6ltazd                                    1.500000   \n",
-       "e57a6qq                                    1.285714   \n",
-       "e5qc7eb                                    1.800000   \n",
-       "e6hqt5y                                    3.000000   \n",
-       "e5ua84v                                    1.500000   \n",
-       "e65m7kq                                    1.800000   \n",
-       "e5ggtru                                    1.800000   \n",
-       "e5pmmig                                    1.125000   \n",
-       "e64l6vq                                    1.500000   \n",
-       "e6fjx0d                                    1.125000   \n",
-       "e5h3xyy                                    1.800000   \n",
-       "e589ri5                                    2.250000   \n",
-       "e5beuqa                                    1.500000   \n",
-       "e5lqoj1                                    1.800000   \n",
-       "e5kvch1                                    1.285714   \n",
-       "e6srvwm                                    1.800000   \n",
-       "e5o65mk                                    1.125000   \n",
-       "e647cm8                                    2.250000   \n",
-       "e58n526                                    9.000000   \n",
-       "e69r2kg                                    1.500000   \n",
+       "e65ca8k                                                0.0       \n",
+       "e6cdkpy                                                1.0       \n",
+       "e5wc4tj                                                4.0       \n",
+       "e6ua0sb                                                2.0       \n",
+       "e5ua84v                                                2.0       \n",
        "\n",
-       "         mean-nonzero[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.500000        \n",
-       "e5ywqyk                                           1.333333        \n",
-       "e5qv9rj                                           1.000000        \n",
-       "e6jhojf                                           1.750000        \n",
-       "e6989ii                                           1.000000        \n",
-       "e69lgse                                           1.200000        \n",
-       "e5kwkg2                                           1.000000        \n",
-       "e6mehe7                                           1.666667        \n",
-       "e6m0hsd                                           1.333333        \n",
-       "e64r385                                           1.166667        \n",
-       "e5surbt                                           1.000000        \n",
-       "e58gxii                                           1.400000        \n",
-       "e64vc8y                                           1.000000        \n",
-       "e57504g                                           1.166667        \n",
-       "e5borjq                                           1.000000        \n",
-       "e64n9zv                                           1.333333        \n",
-       "e582ud3                                           1.000000        \n",
-       "e64i9cf                                           1.333333        \n",
-       "e6q9204                                           1.200000        \n",
-       "e5modd7                                           1.000000        \n",
-       "e5xhbyd                                           1.500000        \n",
-       "e5oaf7h                                           1.333333        \n",
-       "e6nir3u                                           1.000000        \n",
-       "e6c3xdn                                           1.000000        \n",
-       "e5d3zaa                                           1.000000        \n",
-       "e5gnjv9                                           1.000000        \n",
-       "e69gw2t                                           1.250000        \n",
-       "e5syrih                                           1.142857        \n",
-       "e5sa2yf                                           1.000000        \n",
-       "e6ai7z5                                           2.000000        \n",
-       "...                                                    ...        \n",
-       "e5smhzk                                           1.500000        \n",
-       "e5v91s0                                           1.000000        \n",
-       "e6n6di6                                           1.142857        \n",
-       "e6iqq30                                           1.000000        \n",
-       "e5bfad7                                           1.200000        \n",
-       "e6x5he5                                           4.000000        \n",
-       "e6l9uyf                                           1.000000        \n",
-       "e57hyr1                                           1.000000        \n",
-       "e5b8sj7                                           1.000000        \n",
-       "e6nlep7                                           0.000000        \n",
-       "e6ltazd                                           1.000000        \n",
-       "e57a6qq                                           1.200000        \n",
-       "e5qc7eb                                           1.000000        \n",
-       "e6hqt5y                                           1.000000        \n",
-       "e5ua84v                                           1.333333        \n",
-       "e65m7kq                                           1.000000        \n",
-       "e5ggtru                                           1.000000        \n",
-       "e5pmmig                                           1.500000        \n",
-       "e64l6vq                                           1.250000        \n",
-       "e6fjx0d                                           1.000000        \n",
-       "e5h3xyy                                           1.000000        \n",
-       "e589ri5                                           1.000000        \n",
-       "e5beuqa                                           1.400000        \n",
-       "e5lqoj1                                           1.500000        \n",
-       "e5kvch1                                           1.000000        \n",
-       "e6srvwm                                           1.000000        \n",
-       "e5o65mk                                           1.000000        \n",
-       "e647cm8                                           1.000000        \n",
-       "e58n526                                           0.000000        \n",
-       "e69r2kg                                           1.166667        \n",
+       "         2nd-largest[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0      \n",
+       "e5ytz1d                                                2.0      \n",
+       "e6ls80j                                                1.0      \n",
+       "e5mhgl5                                                2.0      \n",
+       "e6w6fah                                                0.0      \n",
+       "...                                                    ...      \n",
+       "e65ca8k                                                1.0      \n",
+       "e6cdkpy                                                2.0      \n",
+       "e5wc4tj                                                1.0      \n",
+       "e6ua0sb                                                1.0      \n",
+       "e5ua84v                                                2.0      \n",
        "\n",
-       "         mean-nonzero[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                     1.333333   \n",
-       "e5ywqyk                                     1.250000   \n",
-       "e5qv9rj                                     1.000000   \n",
-       "e6jhojf                                     1.600000   \n",
-       "e6989ii                                     1.000000   \n",
-       "e69lgse                                     1.142857   \n",
-       "e5kwkg2                                     1.000000   \n",
-       "e6mehe7                                     1.333333   \n",
-       "e6m0hsd                                     1.333333   \n",
-       "e64r385                                     1.285714   \n",
-       "e5surbt                                     1.000000   \n",
-       "e58gxii                                     1.333333   \n",
-       "e64vc8y                                     1.000000   \n",
-       "e57504g                                     1.285714   \n",
-       "e5borjq                                     1.125000   \n",
-       "e64n9zv                                     1.333333   \n",
-       "e582ud3                                     1.000000   \n",
-       "e64i9cf                                     1.166667   \n",
-       "e6q9204                                     1.400000   \n",
-       "e5modd7                                     1.000000   \n",
-       "e5xhbyd                                     1.500000   \n",
-       "e5oaf7h                                     1.333333   \n",
-       "e6nir3u                                     1.000000   \n",
-       "e6c3xdn                                     1.000000   \n",
-       "e5d3zaa                                     1.166667   \n",
-       "e5gnjv9                                     1.125000   \n",
-       "e69gw2t                                     1.400000   \n",
-       "e5syrih                                     1.285714   \n",
-       "e5sa2yf                                     1.000000   \n",
-       "e6ai7z5                                     1.600000   \n",
-       "...                                              ...   \n",
-       "e5smhzk                                     1.333333   \n",
-       "e5v91s0                                     1.000000   \n",
-       "e6n6di6                                     1.125000   \n",
-       "e6iqq30                                     1.000000   \n",
-       "e5bfad7                                     1.125000   \n",
-       "e6x5he5                                     1.600000   \n",
-       "e6l9uyf                                     1.125000   \n",
-       "e57hyr1                                     1.500000   \n",
-       "e5b8sj7                                     1.125000   \n",
-       "e6nlep7                                     1.000000   \n",
-       "e6ltazd                                     1.200000   \n",
-       "e57a6qq                                     1.200000   \n",
-       "e5qc7eb                                     1.166667   \n",
-       "e6hqt5y                                     1.125000   \n",
-       "e5ua84v                                     1.500000   \n",
-       "e65m7kq                                     1.125000   \n",
-       "e5ggtru                                     1.125000   \n",
-       "e5pmmig                                     1.750000   \n",
-       "e64l6vq                                     1.166667   \n",
-       "e6fjx0d                                     1.333333   \n",
-       "e5h3xyy                                     1.125000   \n",
-       "e589ri5                                     1.000000   \n",
-       "e5beuqa                                     1.800000   \n",
-       "e5lqoj1                                     1.333333   \n",
-       "e5kvch1                                     1.333333   \n",
-       "e6srvwm                                     1.125000   \n",
-       "e5o65mk                                     1.000000   \n",
-       "e647cm8                                     1.000000   \n",
-       "e58n526                                     1.000000   \n",
-       "e69r2kg                                     1.125000   \n",
+       "         2nd-argmax[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                2.0      \n",
+       "e5ytz1d                                                4.0      \n",
+       "e6ls80j                                                1.0      \n",
+       "e5mhgl5                                                5.0      \n",
+       "e6w6fah                                                1.0      \n",
+       "...                                                    ...      \n",
+       "e65ca8k                                                0.0      \n",
+       "e6cdkpy                                                3.0      \n",
+       "e5wc4tj                                                1.0      \n",
+       "e6ua0sb                                                4.0      \n",
+       "e5ua84v                                                3.0      \n",
        "\n",
-       "         mean-nonzero[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           1.500000        \n",
-       "e5ywqyk                                           2.666667        \n",
-       "e5qv9rj                                           1.000000        \n",
-       "e6jhojf                                           2.000000        \n",
-       "e6989ii                                           3.500000        \n",
-       "e69lgse                                           1.200000        \n",
-       "e5kwkg2                                           1.000000        \n",
-       "e6mehe7                                           2.000000        \n",
-       "e6m0hsd                                           2.666667        \n",
-       "e64r385                                           1.166667        \n",
-       "e5surbt                                           1.000000        \n",
-       "e58gxii                                           1.400000        \n",
-       "e64vc8y                                           1.000000        \n",
-       "e57504g                                           1.166667        \n",
-       "e5borjq                                           1.000000        \n",
-       "e64n9zv                                           2.666667        \n",
-       "e582ud3                                           1.000000        \n",
-       "e64i9cf                                           1.666667        \n",
-       "e6q9204                                           1.600000        \n",
-       "e5modd7                                           1.000000        \n",
-       "e5xhbyd                                           2.000000        \n",
-       "e5oaf7h                                           2.666667        \n",
-       "e6nir3u                                           3.500000        \n",
-       "e6c3xdn                                           1.000000        \n",
-       "e5d3zaa                                           1.400000        \n",
-       "e5gnjv9                                           1.000000        \n",
-       "e69gw2t                                           1.750000        \n",
-       "e5syrih                                           1.142857        \n",
-       "e5sa2yf                                           4.000000        \n",
-       "e6ai7z5                                           2.000000        \n",
-       "...                                                    ...        \n",
-       "e5smhzk                                           3.500000        \n",
-       "e5v91s0                                           1.000000        \n",
-       "e6n6di6                                           1.142857        \n",
-       "e6iqq30                                           1.000000        \n",
-       "e5bfad7                                           1.200000        \n",
-       "e6x5he5                                           4.000000        \n",
-       "e6l9uyf                                           1.000000        \n",
-       "e57hyr1                                           1.000000        \n",
-       "e5b8sj7                                           1.000000        \n",
-       "e6nlep7                                           0.000000        \n",
-       "e6ltazd                                           1.600000        \n",
-       "e57a6qq                                           1.600000        \n",
-       "e5qc7eb                                           1.166667        \n",
-       "e6hqt5y                                           1.000000        \n",
-       "e5ua84v                                           1.333333        \n",
-       "e65m7kq                                           1.000000        \n",
-       "e5ggtru                                           1.000000        \n",
-       "e5pmmig                                           2.000000        \n",
-       "e64l6vq                                           1.500000        \n",
-       "e6fjx0d                                           3.500000        \n",
-       "e5h3xyy                                           1.000000        \n",
-       "e589ri5                                           1.000000        \n",
-       "e5beuqa                                           1.400000        \n",
-       "e5lqoj1                                           2.000000        \n",
-       "e5kvch1                                           1.200000        \n",
-       "e6srvwm                                           1.000000        \n",
-       "e5o65mk                                           3.500000        \n",
-       "e647cm8                                           1.000000        \n",
-       "e58n526                                           0.000000        \n",
-       "e69r2kg                                           1.166667        \n",
+       "         2nd-argmax[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0     \n",
+       "e5ytz1d                                                0.0     \n",
+       "e6ls80j                                                4.0     \n",
+       "e5mhgl5                                                3.0     \n",
+       "e6w6fah                                                1.0     \n",
+       "...                                                    ...     \n",
+       "e65ca8k                                                2.0     \n",
+       "e6cdkpy                                                1.0     \n",
+       "e5wc4tj                                                1.0     \n",
+       "e6ua0sb                                                0.0     \n",
+       "e5ua84v                                                4.0     \n",
        "\n",
-       "         mean-nonzero[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                     1.500000   \n",
-       "e5ywqyk                                     2.250000   \n",
-       "e5qv9rj                                     1.000000   \n",
-       "e6jhojf                                     1.800000   \n",
-       "e6989ii                                     4.000000   \n",
-       "e69lgse                                     1.285714   \n",
-       "e5kwkg2                                     1.000000   \n",
-       "e6mehe7                                     1.500000   \n",
-       "e6m0hsd                                     3.000000   \n",
-       "e64r385                                     1.285714   \n",
-       "e5surbt                                     1.000000   \n",
-       "e58gxii                                     1.500000   \n",
-       "e64vc8y                                     1.000000   \n",
-       "e57504g                                     1.285714   \n",
-       "e5borjq                                     1.125000   \n",
-       "e64n9zv                                     3.000000   \n",
-       "e582ud3                                     1.000000   \n",
-       "e64i9cf                                     1.500000   \n",
-       "e6q9204                                     1.800000   \n",
-       "e5modd7                                     1.000000   \n",
-       "e5xhbyd                                     2.250000   \n",
-       "e5oaf7h                                     3.000000   \n",
-       "e6nir3u                                     4.000000   \n",
-       "e6c3xdn                                     1.000000   \n",
-       "e5d3zaa                                     1.500000   \n",
-       "e5gnjv9                                     1.125000   \n",
-       "e69gw2t                                     1.800000   \n",
-       "e5syrih                                     1.285714   \n",
-       "e5sa2yf                                     4.500000   \n",
-       "e6ai7z5                                     1.800000   \n",
-       "...                                              ...   \n",
-       "e5smhzk                                     3.000000   \n",
-       "e5v91s0                                     1.000000   \n",
-       "e6n6di6                                     1.125000   \n",
-       "e6iqq30                                     1.000000   \n",
-       "e5bfad7                                     1.125000   \n",
-       "e6x5he5                                     1.600000   \n",
-       "e6l9uyf                                     1.125000   \n",
-       "e57hyr1                                     1.500000   \n",
-       "e5b8sj7                                     1.125000   \n",
-       "e6nlep7                                     1.000000   \n",
-       "e6ltazd                                     1.800000   \n",
-       "e57a6qq                                     1.800000   \n",
-       "e5qc7eb                                     1.500000   \n",
-       "e6hqt5y                                     1.125000   \n",
-       "e5ua84v                                     1.500000   \n",
-       "e65m7kq                                     1.125000   \n",
-       "e5ggtru                                     1.125000   \n",
-       "e5pmmig                                     2.250000   \n",
-       "e64l6vq                                     1.500000   \n",
-       "e6fjx0d                                     3.000000   \n",
-       "e5h3xyy                                     1.125000   \n",
-       "e589ri5                                     1.000000   \n",
-       "e5beuqa                                     1.800000   \n",
-       "e5lqoj1                                     1.500000   \n",
-       "e5kvch1                                     1.500000   \n",
-       "e6srvwm                                     1.125000   \n",
-       "e5o65mk                                     4.000000   \n",
-       "e647cm8                                     1.000000   \n",
-       "e58n526                                     1.000000   \n",
-       "e69r2kg                                     1.125000   \n",
+       "         norm.2nd-largest[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.250000            \n",
+       "e5ytz1d                                           0.166667            \n",
+       "e6ls80j                                           0.200000            \n",
+       "e5mhgl5                                           0.250000            \n",
+       "e6w6fah                                                NaN            \n",
+       "...                                                    ...            \n",
+       "e65ca8k                                           0.000000            \n",
+       "e6cdkpy                                           0.200000            \n",
+       "e5wc4tj                                           0.500000            \n",
+       "e6ua0sb                                           0.285714            \n",
+       "e5ua84v                                           0.250000            \n",
        "\n",
-       "         mean[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                       1.000000   \n",
-       "e5ywqyk                                       1.000000   \n",
-       "e5qv9rj                                       0.666667   \n",
-       "e6jhojf                                       1.400000   \n",
-       "e6989ii                                       1.000000   \n",
-       "e69lgse                                       0.857143   \n",
-       "e5kwkg2                                       0.666667   \n",
-       "e6mehe7                                       0.833333   \n",
-       "e6m0hsd                                       1.333333   \n",
-       "e64r385                                       1.000000   \n",
-       "e5surbt                                       0.444444   \n",
-       "e58gxii                                       1.166667   \n",
-       "e64vc8y                                       0.333333   \n",
-       "e57504g                                       1.000000   \n",
-       "e5borjq                                       0.875000   \n",
-       "e64n9zv                                       1.333333   \n",
-       "e582ud3                                       0.333333   \n",
-       "e64i9cf                                       0.666667   \n",
-       "e6q9204                                       1.200000   \n",
-       "e5modd7                                       0.888889   \n",
-       "e5xhbyd                                       1.500000   \n",
-       "e5oaf7h                                       1.333333   \n",
-       "e6nir3u                                       1.000000   \n",
-       "e6c3xdn                                       0.888889   \n",
-       "e5d3zaa                                       0.833333   \n",
-       "e5gnjv9                                       0.125000   \n",
-       "e69gw2t                                       1.000000   \n",
-       "e5syrih                                       1.142857   \n",
-       "e5sa2yf                                       1.000000   \n",
-       "e6ai7z5                                       1.200000   \n",
-       "...                                                ...   \n",
-       "e5smhzk                                       1.000000   \n",
-       "e5v91s0                                       0.444444   \n",
-       "e6n6di6                                       1.000000   \n",
-       "e6iqq30                                       0.333333   \n",
-       "e5bfad7                                       0.750000   \n",
-       "e6x5he5                                       0.800000   \n",
-       "e6l9uyf                                       0.500000   \n",
-       "e57hyr1                                       0.833333   \n",
-       "e5b8sj7                                       0.750000   \n",
-       "e6nlep7                                       0.000000   \n",
-       "e6ltazd                                       1.000000   \n",
-       "e57a6qq                                       1.200000   \n",
-       "e5qc7eb                                       1.000000   \n",
-       "e6hqt5y                                       0.625000   \n",
-       "e5ua84v                                       1.333333   \n",
-       "e65m7kq                                       0.625000   \n",
-       "e5ggtru                                       1.000000   \n",
-       "e5pmmig                                       1.500000   \n",
-       "e64l6vq                                       0.833333   \n",
-       "e6fjx0d                                       0.666667   \n",
-       "e5h3xyy                                       0.625000   \n",
-       "e589ri5                                       0.333333   \n",
-       "e5beuqa                                       1.400000   \n",
-       "e5lqoj1                                       0.500000   \n",
-       "e5kvch1                                       0.833333   \n",
-       "e6srvwm                                       0.750000   \n",
-       "e5o65mk                                       1.000000   \n",
-       "e647cm8                                       0.555556   \n",
-       "e58n526                                       0.000000   \n",
-       "e69r2kg                                       0.875000   \n",
+       "         norm.2nd-largest[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.125000           \n",
+       "e5ytz1d                                           0.333333           \n",
+       "e6ls80j                                           0.200000           \n",
+       "e5mhgl5                                           0.250000           \n",
+       "e6w6fah                                                NaN           \n",
+       "...                                                    ...           \n",
+       "e65ca8k                                           0.142857           \n",
+       "e6cdkpy                                           0.400000           \n",
+       "e5wc4tj                                           0.125000           \n",
+       "e6ua0sb                                           0.142857           \n",
+       "e5ua84v                                           0.250000           \n",
        "\n",
-       "         mean[indegree over C->C responses]  \\\n",
-       "e6p7yrp                            1.333333   \n",
-       "e5ywqyk                            1.250000   \n",
-       "e5qv9rj                            0.900000   \n",
-       "e6jhojf                            1.600000   \n",
-       "e6989ii                            1.000000   \n",
-       "e69lgse                            1.142857   \n",
-       "e5kwkg2                            0.900000   \n",
-       "e6mehe7                            1.333333   \n",
-       "e6m0hsd                            1.333333   \n",
-       "e64r385                            1.125000   \n",
-       "e5surbt                            0.900000   \n",
-       "e58gxii                            1.333333   \n",
-       "e64vc8y                            0.900000   \n",
-       "e57504g                            1.125000   \n",
-       "e5borjq                            1.125000   \n",
-       "e64n9zv                            1.333333   \n",
-       "e582ud3                            0.900000   \n",
-       "e64i9cf                            1.166667   \n",
-       "e6q9204                            1.166667   \n",
-       "e5modd7                            0.900000   \n",
-       "e5xhbyd                            1.500000   \n",
-       "e5oaf7h                            1.333333   \n",
-       "e6nir3u                            1.000000   \n",
-       "e6c3xdn                            0.900000   \n",
-       "e5d3zaa                            1.000000   \n",
-       "e5gnjv9                            1.000000   \n",
-       "e69gw2t                            1.400000   \n",
-       "e5syrih                            1.285714   \n",
-       "e5sa2yf                            1.000000   \n",
-       "e6ai7z5                            1.600000   \n",
-       "...                                     ...   \n",
-       "e5smhzk                            1.333333   \n",
-       "e5v91s0                            0.900000   \n",
-       "e6n6di6                            1.000000   \n",
-       "e6iqq30                            1.000000   \n",
-       "e5bfad7                            1.125000   \n",
-       "e6x5he5                            1.600000   \n",
-       "e6l9uyf                            1.000000   \n",
-       "e57hyr1                            1.285714   \n",
-       "e5b8sj7                            1.125000   \n",
-       "e6nlep7                            0.900000   \n",
-       "e6ltazd                            1.000000   \n",
-       "e57a6qq                            1.200000   \n",
-       "e5qc7eb                            1.166667   \n",
-       "e6hqt5y                            1.000000   \n",
-       "e5ua84v                            1.285714   \n",
-       "e65m7kq                            1.000000   \n",
-       "e5ggtru                            1.000000   \n",
-       "e5pmmig                            1.400000   \n",
-       "e64l6vq                            1.166667   \n",
-       "e6fjx0d                            1.000000   \n",
-       "e5h3xyy                            1.000000   \n",
-       "e589ri5                            0.900000   \n",
-       "e5beuqa                            1.500000   \n",
-       "e5lqoj1                            1.142857   \n",
-       "e5kvch1                            1.142857   \n",
-       "e6srvwm                            1.000000   \n",
-       "e5o65mk                            1.000000   \n",
-       "e647cm8                            1.000000   \n",
-       "e58n526                            0.900000   \n",
-       "e69r2kg                            1.125000   \n",
+       "         mean[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                        1.600000   \n",
+       "e5ytz1d                                        0.666667   \n",
+       "e6ls80j                                        0.833333   \n",
+       "e5mhgl5                                        1.142857   \n",
+       "e6w6fah                                        0.000000   \n",
+       "...                                                 ...   \n",
+       "e65ca8k                                        3.500000   \n",
+       "e6cdkpy                                        0.555556   \n",
+       "e5wc4tj                                        4.000000   \n",
+       "e6ua0sb                                        1.400000   \n",
+       "e5ua84v                                        1.333333   \n",
        "\n",
        "         mean[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                       0.666667   \n",
-       "e5ywqyk                                       0.888889   \n",
-       "e5qv9rj                                       0.666667   \n",
-       "e6jhojf                                       0.888889   \n",
-       "e6989ii                                       0.777778   \n",
-       "e69lgse                                       0.666667   \n",
-       "e5kwkg2                                       0.666667   \n",
-       "e6mehe7                                       0.666667   \n",
-       "e6m0hsd                                       0.888889   \n",
-       "e64r385                                       0.777778   \n",
-       "e5surbt                                       0.444444   \n",
-       "e58gxii                                       0.777778   \n",
-       "e64vc8y                                       0.333333   \n",
-       "e57504g                                       0.777778   \n",
-       "e5borjq                                       0.777778   \n",
-       "e64n9zv                                       0.888889   \n",
-       "e582ud3                                       0.333333   \n",
-       "e64i9cf                                       0.555556   \n",
-       "e6q9204                                       0.888889   \n",
-       "e5modd7                                       0.888889   \n",
-       "e5xhbyd                                       0.888889   \n",
-       "e5oaf7h                                       0.888889   \n",
-       "e6nir3u                                       0.777778   \n",
-       "e6c3xdn                                       0.888889   \n",
-       "e5d3zaa                                       0.777778   \n",
-       "e5gnjv9                                       0.111111   \n",
-       "e69gw2t                                       0.777778   \n",
-       "e5syrih                                       0.888889   \n",
-       "e5sa2yf                                       0.888889   \n",
-       "e6ai7z5                                       0.666667   \n",
-       "...                                                ...   \n",
-       "e5smhzk                                       0.777778   \n",
-       "e5v91s0                                       0.444444   \n",
-       "e6n6di6                                       0.888889   \n",
-       "e6iqq30                                       0.333333   \n",
-       "e5bfad7                                       0.666667   \n",
-       "e6x5he5                                       0.444444   \n",
-       "e6l9uyf                                       0.444444   \n",
-       "e57hyr1                                       0.555556   \n",
-       "e5b8sj7                                       0.666667   \n",
-       "e6nlep7                                       0.000000   \n",
-       "e6ltazd                                       0.888889   \n",
-       "e57a6qq                                       0.888889   \n",
-       "e5qc7eb                                       0.777778   \n",
-       "e6hqt5y                                       0.555556   \n",
-       "e5ua84v                                       0.888889   \n",
-       "e65m7kq                                       0.555556   \n",
-       "e5ggtru                                       0.888889   \n",
-       "e5pmmig                                       0.888889   \n",
-       "e64l6vq                                       0.666667   \n",
-       "e6fjx0d                                       0.777778   \n",
-       "e5h3xyy                                       0.555556   \n",
-       "e589ri5                                       0.333333   \n",
-       "e5beuqa                                       0.777778   \n",
-       "e5lqoj1                                       0.444444   \n",
-       "e5kvch1                                       0.666667   \n",
-       "e6srvwm                                       0.666667   \n",
-       "e5o65mk                                       0.777778   \n",
-       "e647cm8                                       0.555556   \n",
-       "e58n526                                       0.000000   \n",
-       "e69r2kg                                       0.777778   \n",
-       "\n",
-       "         mean[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                 0.9   \n",
-       "e5ywqyk                                 0.9   \n",
-       "e5qv9rj                                 0.9   \n",
-       "e6jhojf                                 0.9   \n",
-       "e6989ii                                 0.8   \n",
-       "e69lgse                                 0.9   \n",
-       "e5kwkg2                                 0.9   \n",
-       "e6mehe7                                 0.9   \n",
-       "e6m0hsd                                 0.9   \n",
-       "e64r385                                 0.9   \n",
-       "e5surbt                                 0.9   \n",
-       "e58gxii                                 0.9   \n",
-       "e64vc8y                                 0.9   \n",
-       "e57504g                                 0.9   \n",
-       "e5borjq                                 0.9   \n",
-       "e64n9zv                                 0.9   \n",
-       "e582ud3                                 0.9   \n",
-       "e64i9cf                                 0.9   \n",
-       "e6q9204                                 0.9   \n",
-       "e5modd7                                 0.9   \n",
-       "e5xhbyd                                 0.9   \n",
-       "e5oaf7h                                 0.9   \n",
-       "e6nir3u                                 0.8   \n",
-       "e6c3xdn                                 0.9   \n",
-       "e5d3zaa                                 0.9   \n",
-       "e5gnjv9                                 0.9   \n",
-       "e69gw2t                                 0.9   \n",
-       "e5syrih                                 0.9   \n",
-       "e5sa2yf                                 0.9   \n",
-       "e6ai7z5                                 0.9   \n",
-       "...                                     ...   \n",
-       "e5smhzk                                 0.9   \n",
-       "e5v91s0                                 0.9   \n",
-       "e6n6di6                                 0.9   \n",
-       "e6iqq30                                 0.9   \n",
-       "e5bfad7                                 0.9   \n",
-       "e6x5he5                                 0.8   \n",
-       "e6l9uyf                                 0.9   \n",
-       "e57hyr1                                 0.9   \n",
-       "e5b8sj7                                 0.9   \n",
-       "e6nlep7                                 0.9   \n",
-       "e6ltazd                                 0.9   \n",
-       "e57a6qq                                 0.9   \n",
-       "e5qc7eb                                 0.9   \n",
-       "e6hqt5y                                 0.9   \n",
-       "e5ua84v                                 0.9   \n",
-       "e65m7kq                                 0.9   \n",
-       "e5ggtru                                 0.9   \n",
-       "e5pmmig                                 0.9   \n",
-       "e64l6vq                                 0.9   \n",
-       "e6fjx0d                                 0.9   \n",
-       "e5h3xyy                                 0.9   \n",
-       "e589ri5                                 0.9   \n",
-       "e5beuqa                                 0.9   \n",
-       "e5lqoj1                                 0.9   \n",
-       "e5kvch1                                 0.9   \n",
-       "e6srvwm                                 0.9   \n",
-       "e5o65mk                                 0.8   \n",
-       "e647cm8                                 0.9   \n",
-       "e58n526                                 0.9   \n",
-       "e69r2kg                                 0.9   \n",
-       "\n",
-       "         mean[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                       0.666667   \n",
-       "e5ywqyk                                       0.888889   \n",
-       "e5qv9rj                                       0.666667   \n",
-       "e6jhojf                                       0.888889   \n",
-       "e6989ii                                       0.888889   \n",
-       "e69lgse                                       0.666667   \n",
-       "e5kwkg2                                       0.666667   \n",
-       "e6mehe7                                       0.666667   \n",
-       "e6m0hsd                                       0.888889   \n",
-       "e64r385                                       0.777778   \n",
-       "e5surbt                                       0.444444   \n",
-       "e58gxii                                       0.777778   \n",
-       "e64vc8y                                       0.333333   \n",
-       "e57504g                                       0.777778   \n",
-       "e5borjq                                       0.777778   \n",
-       "e64n9zv                                       0.888889   \n",
-       "e582ud3                                       0.333333   \n",
-       "e64i9cf                                       0.555556   \n",
-       "e6q9204                                       0.888889   \n",
-       "e5modd7                                       0.888889   \n",
-       "e5xhbyd                                       0.888889   \n",
-       "e5oaf7h                                       0.888889   \n",
-       "e6nir3u                                       0.888889   \n",
-       "e6c3xdn                                       0.888889   \n",
-       "e5d3zaa                                       0.777778   \n",
-       "e5gnjv9                                       0.111111   \n",
-       "e69gw2t                                       0.777778   \n",
-       "e5syrih                                       0.888889   \n",
-       "e5sa2yf                                       0.888889   \n",
-       "e6ai7z5                                       0.666667   \n",
+       "e5hm9mp                                       0.888889   \n",
+       "e5ytz1d                                       0.666667   \n",
+       "e6ls80j                                       0.555556   \n",
+       "e5mhgl5                                       0.888889   \n",
+       "e6w6fah                                       0.000000   \n",
        "...                                                ...   \n",
-       "e5smhzk                                       0.777778   \n",
-       "e5v91s0                                       0.444444   \n",
-       "e6n6di6                                       0.888889   \n",
-       "e6iqq30                                       0.333333   \n",
-       "e5bfad7                                       0.666667   \n",
-       "e6x5he5                                       0.555556   \n",
-       "e6l9uyf                                       0.444444   \n",
-       "e57hyr1                                       0.555556   \n",
-       "e5b8sj7                                       0.666667   \n",
-       "e6nlep7                                       0.000000   \n",
-       "e6ltazd                                       0.888889   \n",
-       "e57a6qq                                       0.888889   \n",
-       "e5qc7eb                                       0.777778   \n",
-       "e6hqt5y                                       0.555556   \n",
+       "e65ca8k                                       0.777778   \n",
+       "e6cdkpy                                       0.555556   \n",
+       "e5wc4tj                                       0.888889   \n",
+       "e6ua0sb                                       0.777778   \n",
        "e5ua84v                                       0.888889   \n",
-       "e65m7kq                                       0.555556   \n",
-       "e5ggtru                                       0.888889   \n",
-       "e5pmmig                                       0.888889   \n",
-       "e64l6vq                                       0.666667   \n",
-       "e6fjx0d                                       0.777778   \n",
-       "e5h3xyy                                       0.555556   \n",
-       "e589ri5                                       0.333333   \n",
-       "e5beuqa                                       0.777778   \n",
-       "e5lqoj1                                       0.444444   \n",
-       "e5kvch1                                       0.666667   \n",
-       "e6srvwm                                       0.666667   \n",
-       "e5o65mk                                       0.777778   \n",
-       "e647cm8                                       0.555556   \n",
-       "e58n526                                       0.000000   \n",
-       "e69r2kg                                       0.777778   \n",
-       "\n",
-       "         mean[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                 0.9   \n",
-       "e5ywqyk                                 0.9   \n",
-       "e5qv9rj                                 0.9   \n",
-       "e6jhojf                                 0.9   \n",
-       "e6989ii                                 0.9   \n",
-       "e69lgse                                 0.9   \n",
-       "e5kwkg2                                 0.9   \n",
-       "e6mehe7                                 0.9   \n",
-       "e6m0hsd                                 0.9   \n",
-       "e64r385                                 0.9   \n",
-       "e5surbt                                 0.9   \n",
-       "e58gxii                                 0.9   \n",
-       "e64vc8y                                 0.9   \n",
-       "e57504g                                 0.9   \n",
-       "e5borjq                                 0.9   \n",
-       "e64n9zv                                 0.9   \n",
-       "e582ud3                                 0.9   \n",
-       "e64i9cf                                 0.9   \n",
-       "e6q9204                                 0.9   \n",
-       "e5modd7                                 0.9   \n",
-       "e5xhbyd                                 0.9   \n",
-       "e5oaf7h                                 0.9   \n",
-       "e6nir3u                                 0.9   \n",
-       "e6c3xdn                                 0.9   \n",
-       "e5d3zaa                                 0.9   \n",
-       "e5gnjv9                                 0.9   \n",
-       "e69gw2t                                 0.9   \n",
-       "e5syrih                                 0.9   \n",
-       "e5sa2yf                                 0.9   \n",
-       "e6ai7z5                                 0.9   \n",
-       "...                                     ...   \n",
-       "e5smhzk                                 0.9   \n",
-       "e5v91s0                                 0.9   \n",
-       "e6n6di6                                 0.9   \n",
-       "e6iqq30                                 0.9   \n",
-       "e5bfad7                                 0.9   \n",
-       "e6x5he5                                 0.9   \n",
-       "e6l9uyf                                 0.9   \n",
-       "e57hyr1                                 0.9   \n",
-       "e5b8sj7                                 0.9   \n",
-       "e6nlep7                                 0.9   \n",
-       "e6ltazd                                 0.9   \n",
-       "e57a6qq                                 0.9   \n",
-       "e5qc7eb                                 0.9   \n",
-       "e6hqt5y                                 0.9   \n",
-       "e5ua84v                                 0.9   \n",
-       "e65m7kq                                 0.9   \n",
-       "e5ggtru                                 0.9   \n",
-       "e5pmmig                                 0.9   \n",
-       "e64l6vq                                 0.9   \n",
-       "e6fjx0d                                 0.9   \n",
-       "e5h3xyy                                 0.9   \n",
-       "e589ri5                                 0.9   \n",
-       "e5beuqa                                 0.9   \n",
-       "e5lqoj1                                 0.9   \n",
-       "e5kvch1                                 0.9   \n",
-       "e6srvwm                                 0.9   \n",
-       "e5o65mk                                 0.9   \n",
-       "e647cm8                                 0.9   \n",
-       "e58n526                                 0.9   \n",
-       "e69r2kg                                 0.9   \n",
-       "\n",
-       "         mean[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                        1.000000   \n",
-       "e5ywqyk                                        1.000000   \n",
-       "e5qv9rj                                        0.666667   \n",
-       "e6jhojf                                        1.400000   \n",
-       "e6989ii                                        1.000000   \n",
-       "e69lgse                                        0.857143   \n",
-       "e5kwkg2                                        0.666667   \n",
-       "e6mehe7                                        0.833333   \n",
-       "e6m0hsd                                        1.333333   \n",
-       "e64r385                                        1.000000   \n",
-       "e5surbt                                        0.444444   \n",
-       "e58gxii                                        1.166667   \n",
-       "e64vc8y                                        0.333333   \n",
-       "e57504g                                        1.000000   \n",
-       "e5borjq                                        0.875000   \n",
-       "e64n9zv                                        1.333333   \n",
-       "e582ud3                                        0.333333   \n",
-       "e64i9cf                                        0.666667   \n",
-       "e6q9204                                        1.200000   \n",
-       "e5modd7                                        0.888889   \n",
-       "e5xhbyd                                        1.500000   \n",
-       "e5oaf7h                                        1.333333   \n",
-       "e6nir3u                                        1.000000   \n",
-       "e6c3xdn                                        0.888889   \n",
-       "e5d3zaa                                        0.833333   \n",
-       "e5gnjv9                                        0.125000   \n",
-       "e69gw2t                                        1.000000   \n",
-       "e5syrih                                        1.142857   \n",
-       "e5sa2yf                                        1.000000   \n",
-       "e6ai7z5                                        1.200000   \n",
-       "...                                                 ...   \n",
-       "e5smhzk                                        1.000000   \n",
-       "e5v91s0                                        0.444444   \n",
-       "e6n6di6                                        1.000000   \n",
-       "e6iqq30                                        0.333333   \n",
-       "e5bfad7                                        0.750000   \n",
-       "e6x5he5                                        0.800000   \n",
-       "e6l9uyf                                        0.500000   \n",
-       "e57hyr1                                        0.833333   \n",
-       "e5b8sj7                                        0.750000   \n",
-       "e6nlep7                                        0.000000   \n",
-       "e6ltazd                                        1.000000   \n",
-       "e57a6qq                                        1.200000   \n",
-       "e5qc7eb                                        1.000000   \n",
-       "e6hqt5y                                        0.625000   \n",
-       "e5ua84v                                        1.333333   \n",
-       "e65m7kq                                        0.625000   \n",
-       "e5ggtru                                        1.000000   \n",
-       "e5pmmig                                        1.500000   \n",
-       "e64l6vq                                        0.833333   \n",
-       "e6fjx0d                                        0.666667   \n",
-       "e5h3xyy                                        0.625000   \n",
-       "e589ri5                                        0.333333   \n",
-       "e5beuqa                                        1.400000   \n",
-       "e5lqoj1                                        0.500000   \n",
-       "e5kvch1                                        0.833333   \n",
-       "e6srvwm                                        0.750000   \n",
-       "e5o65mk                                        1.000000   \n",
-       "e647cm8                                        0.555556   \n",
-       "e58n526                                        0.000000   \n",
-       "e69r2kg                                        0.875000   \n",
        "\n",
-       "         mean[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                             1.333333   \n",
-       "e5ywqyk                             1.250000   \n",
-       "e5qv9rj                             0.900000   \n",
-       "e6jhojf                             1.600000   \n",
-       "e6989ii                             1.000000   \n",
-       "e69lgse                             1.142857   \n",
-       "e5kwkg2                             0.900000   \n",
-       "e6mehe7                             1.333333   \n",
-       "e6m0hsd                             1.333333   \n",
-       "e64r385                             1.125000   \n",
-       "e5surbt                             0.900000   \n",
-       "e58gxii                             1.333333   \n",
-       "e64vc8y                             0.900000   \n",
-       "e57504g                             1.125000   \n",
-       "e5borjq                             1.125000   \n",
-       "e64n9zv                             1.333333   \n",
-       "e582ud3                             0.900000   \n",
-       "e64i9cf                             1.166667   \n",
-       "e6q9204                             1.166667   \n",
-       "e5modd7                             0.900000   \n",
-       "e5xhbyd                             1.500000   \n",
-       "e5oaf7h                             1.333333   \n",
-       "e6nir3u                             1.000000   \n",
-       "e6c3xdn                             0.900000   \n",
-       "e5d3zaa                             1.000000   \n",
-       "e5gnjv9                             1.000000   \n",
-       "e69gw2t                             1.400000   \n",
-       "e5syrih                             1.285714   \n",
-       "e5sa2yf                             1.000000   \n",
-       "e6ai7z5                             1.600000   \n",
-       "...                                      ...   \n",
-       "e5smhzk                             1.333333   \n",
-       "e5v91s0                             0.900000   \n",
-       "e6n6di6                             1.000000   \n",
-       "e6iqq30                             1.000000   \n",
-       "e5bfad7                             1.125000   \n",
-       "e6x5he5                             1.600000   \n",
-       "e6l9uyf                             1.000000   \n",
-       "e57hyr1                             1.285714   \n",
-       "e5b8sj7                             1.125000   \n",
-       "e6nlep7                             0.900000   \n",
-       "e6ltazd                             1.000000   \n",
-       "e57a6qq                             1.200000   \n",
-       "e5qc7eb                             1.166667   \n",
-       "e6hqt5y                             1.000000   \n",
-       "e5ua84v                             1.285714   \n",
-       "e65m7kq                             1.000000   \n",
-       "e5ggtru                             1.000000   \n",
-       "e5pmmig                             1.400000   \n",
-       "e64l6vq                             1.166667   \n",
-       "e6fjx0d                             1.000000   \n",
-       "e5h3xyy                             1.000000   \n",
-       "e589ri5                             0.900000   \n",
-       "e5beuqa                             1.500000   \n",
-       "e5lqoj1                             1.142857   \n",
-       "e5kvch1                             1.142857   \n",
-       "e6srvwm                             1.000000   \n",
-       "e5o65mk                             1.000000   \n",
-       "e647cm8                             1.000000   \n",
-       "e58n526                             0.900000   \n",
-       "e69r2kg                             1.125000   \n",
+       "         mean-nonzero[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           2.000000        \n",
+       "e5ytz1d                                           1.000000        \n",
+       "e6ls80j                                           1.250000        \n",
+       "e5mhgl5                                           1.333333        \n",
+       "e6w6fah                                           0.000000        \n",
+       "...                                                    ...        \n",
+       "e65ca8k                                           7.000000        \n",
+       "e6cdkpy                                           1.000000        \n",
+       "e5wc4tj                                           4.000000        \n",
+       "e6ua0sb                                           1.400000        \n",
+       "e5ua84v                                           1.333333        \n",
        "\n",
-       "         mean[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                        1.000000   \n",
-       "e5ywqyk                                        2.000000   \n",
-       "e5qv9rj                                        0.666667   \n",
-       "e6jhojf                                        1.600000   \n",
-       "e6989ii                                        3.500000   \n",
-       "e69lgse                                        0.857143   \n",
-       "e5kwkg2                                        0.666667   \n",
-       "e6mehe7                                        1.000000   \n",
-       "e6m0hsd                                        2.666667   \n",
-       "e64r385                                        1.000000   \n",
-       "e5surbt                                        0.444444   \n",
-       "e58gxii                                        1.166667   \n",
-       "e64vc8y                                        0.333333   \n",
-       "e57504g                                        1.000000   \n",
-       "e5borjq                                        0.875000   \n",
-       "e64n9zv                                        2.666667   \n",
-       "e582ud3                                        0.333333   \n",
-       "e64i9cf                                        0.833333   \n",
-       "e6q9204                                        1.600000   \n",
-       "e5modd7                                        0.888889   \n",
-       "e5xhbyd                                        2.000000   \n",
-       "e5oaf7h                                        2.666667   \n",
-       "e6nir3u                                        3.500000   \n",
-       "e6c3xdn                                        0.888889   \n",
-       "e5d3zaa                                        1.166667   \n",
-       "e5gnjv9                                        0.125000   \n",
-       "e69gw2t                                        1.400000   \n",
-       "e5syrih                                        1.142857   \n",
-       "e5sa2yf                                        4.000000   \n",
-       "e6ai7z5                                        1.200000   \n",
-       "...                                                 ...   \n",
-       "e5smhzk                                        2.333333   \n",
-       "e5v91s0                                        0.444444   \n",
-       "e6n6di6                                        1.000000   \n",
-       "e6iqq30                                        0.333333   \n",
-       "e5bfad7                                        0.750000   \n",
-       "e6x5he5                                        0.800000   \n",
-       "e6l9uyf                                        0.500000   \n",
-       "e57hyr1                                        0.833333   \n",
-       "e5b8sj7                                        0.750000   \n",
-       "e6nlep7                                        0.000000   \n",
-       "e6ltazd                                        1.600000   \n",
-       "e57a6qq                                        1.600000   \n",
-       "e5qc7eb                                        1.166667   \n",
-       "e6hqt5y                                        0.625000   \n",
-       "e5ua84v                                        1.333333   \n",
-       "e65m7kq                                        0.625000   \n",
-       "e5ggtru                                        1.000000   \n",
-       "e5pmmig                                        2.000000   \n",
-       "e64l6vq                                        1.000000   \n",
-       "e6fjx0d                                        2.333333   \n",
-       "e5h3xyy                                        0.625000   \n",
-       "e589ri5                                        0.333333   \n",
-       "e5beuqa                                        1.400000   \n",
-       "e5lqoj1                                        0.666667   \n",
-       "e5kvch1                                        1.000000   \n",
-       "e6srvwm                                        0.750000   \n",
-       "e5o65mk                                        3.500000   \n",
-       "e647cm8                                        0.555556   \n",
-       "e58n526                                        0.000000   \n",
-       "e69r2kg                                        0.875000   \n",
+       "         mean-nonzero[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.333333       \n",
+       "e5ytz1d                                           2.000000       \n",
+       "e6ls80j                                           1.666667       \n",
+       "e5mhgl5                                           1.333333       \n",
+       "e6w6fah                                           0.000000       \n",
+       "...                                                    ...       \n",
+       "e65ca8k                                           1.000000       \n",
+       "e6cdkpy                                           1.666667       \n",
+       "e5wc4tj                                           1.000000       \n",
+       "e6ua0sb                                           1.750000       \n",
+       "e5ua84v                                           1.600000       \n",
        "\n",
-       "         mean[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                             1.500000   \n",
-       "e5ywqyk                             2.250000   \n",
-       "e5qv9rj                             0.900000   \n",
-       "e6jhojf                             1.800000   \n",
-       "e6989ii                             4.000000   \n",
-       "e69lgse                             1.285714   \n",
-       "e5kwkg2                             0.900000   \n",
-       "e6mehe7                             1.500000   \n",
-       "e6m0hsd                             3.000000   \n",
-       "e64r385                             1.125000   \n",
-       "e5surbt                             0.900000   \n",
-       "e58gxii                             1.500000   \n",
-       "e64vc8y                             0.900000   \n",
-       "e57504g                             1.125000   \n",
-       "e5borjq                             1.125000   \n",
-       "e64n9zv                             3.000000   \n",
-       "e582ud3                             0.900000   \n",
-       "e64i9cf                             1.500000   \n",
-       "e6q9204                             1.500000   \n",
-       "e5modd7                             0.900000   \n",
-       "e5xhbyd                             2.250000   \n",
-       "e5oaf7h                             3.000000   \n",
-       "e6nir3u                             4.000000   \n",
-       "e6c3xdn                             0.900000   \n",
-       "e5d3zaa                             1.285714   \n",
-       "e5gnjv9                             1.000000   \n",
-       "e69gw2t                             1.800000   \n",
-       "e5syrih                             1.285714   \n",
-       "e5sa2yf                             4.500000   \n",
-       "e6ai7z5                             1.800000   \n",
-       "...                                      ...   \n",
-       "e5smhzk                             3.000000   \n",
-       "e5v91s0                             0.900000   \n",
-       "e6n6di6                             1.000000   \n",
-       "e6iqq30                             1.000000   \n",
-       "e5bfad7                             1.125000   \n",
-       "e6x5he5                             1.600000   \n",
-       "e6l9uyf                             1.000000   \n",
-       "e57hyr1                             1.285714   \n",
-       "e5b8sj7                             1.125000   \n",
-       "e6nlep7                             0.900000   \n",
-       "e6ltazd                             1.500000   \n",
-       "e57a6qq                             1.800000   \n",
-       "e5qc7eb                             1.500000   \n",
-       "e6hqt5y                             1.000000   \n",
-       "e5ua84v                             1.285714   \n",
-       "e65m7kq                             1.000000   \n",
-       "e5ggtru                             1.000000   \n",
-       "e5pmmig                             1.800000   \n",
-       "e64l6vq                             1.500000   \n",
-       "e6fjx0d                             2.250000   \n",
-       "e5h3xyy                             1.000000   \n",
-       "e589ri5                             0.900000   \n",
-       "e5beuqa                             1.500000   \n",
-       "e5lqoj1                             1.285714   \n",
-       "e5kvch1                             1.285714   \n",
-       "e6srvwm                             1.000000   \n",
-       "e5o65mk                             4.000000   \n",
-       "e647cm8                             1.000000   \n",
-       "e58n526                             0.900000   \n",
-       "e69r2kg                             1.125000   \n",
+       "         prop-nonzero[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.800000        \n",
+       "e5ytz1d                                           0.666667        \n",
+       "e6ls80j                                           0.666667        \n",
+       "e5mhgl5                                           0.857143        \n",
+       "e6w6fah                                           0.000000        \n",
+       "...                                                    ...        \n",
+       "e65ca8k                                           0.500000        \n",
+       "e6cdkpy                                           0.555556        \n",
+       "e5wc4tj                                           1.000000        \n",
+       "e6ua0sb                                           1.000000        \n",
+       "e5ua84v                                           1.000000        \n",
        "\n",
-       "         norm.2nd-largest[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667           \n",
-       "e5ywqyk                                           0.250000           \n",
-       "e5qv9rj                                           0.166667           \n",
-       "e6jhojf                                           0.142857           \n",
-       "e6989ii                                           0.500000           \n",
-       "e69lgse                                           0.166667           \n",
-       "e5kwkg2                                           0.166667           \n",
-       "e6mehe7                                           0.200000           \n",
-       "e6m0hsd                                           0.250000           \n",
-       "e64r385                                           0.285714           \n",
-       "e5surbt                                           0.250000           \n",
-       "e58gxii                                           0.285714           \n",
-       "e64vc8y                                           0.333333           \n",
-       "e57504g                                           0.285714           \n",
-       "e5borjq                                           0.285714           \n",
-       "e64n9zv                                           0.250000           \n",
-       "e582ud3                                           0.333333           \n",
-       "e64i9cf                                           0.250000           \n",
-       "e6q9204                                           0.333333           \n",
-       "e5modd7                                           0.250000           \n",
-       "e5xhbyd                                           0.333333           \n",
-       "e5oaf7h                                           0.250000           \n",
-       "e6nir3u                                           0.500000           \n",
-       "e6c3xdn                                           0.125000           \n",
-       "e5d3zaa                                           0.400000           \n",
-       "e5gnjv9                                           0.000000           \n",
-       "e69gw2t                                           0.400000           \n",
-       "e5syrih                                           0.250000           \n",
-       "e5sa2yf                                           0.500000           \n",
-       "e6ai7z5                                           0.166667           \n",
-       "...                                                    ...           \n",
-       "e5smhzk                                           0.333333           \n",
-       "e5v91s0                                           0.250000           \n",
-       "e6n6di6                                           0.250000           \n",
-       "e6iqq30                                           0.333333           \n",
-       "e5bfad7                                           0.333333           \n",
-       "e6x5he5                                           0.250000           \n",
-       "e6l9uyf                                           0.250000           \n",
-       "e57hyr1                                           0.200000           \n",
-       "e5b8sj7                                           0.333333           \n",
-       "e6nlep7                                                NaN           \n",
-       "e6ltazd                                           0.200000           \n",
-       "e57a6qq                                           0.333333           \n",
-       "e5qc7eb                                           0.333333           \n",
-       "e6hqt5y                                           0.200000           \n",
-       "e5ua84v                                           0.250000           \n",
-       "e65m7kq                                           0.200000           \n",
-       "e5ggtru                                           0.250000           \n",
-       "e5pmmig                                           0.333333           \n",
-       "e64l6vq                                           0.200000           \n",
-       "e6fjx0d                                           0.500000           \n",
-       "e5h3xyy                                           0.200000           \n",
-       "e589ri5                                           0.333333           \n",
-       "e5beuqa                                           0.142857           \n",
-       "e5lqoj1                                           0.333333           \n",
-       "e5kvch1                                           0.200000           \n",
-       "e6srvwm                                           0.333333           \n",
-       "e5o65mk                                           0.500000           \n",
-       "e647cm8                                           0.200000           \n",
-       "e58n526                                                NaN           \n",
-       "e69r2kg                                           0.285714           \n",
+       "         prop-nonzero[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.666667       \n",
+       "e5ytz1d                                           0.333333       \n",
+       "e6ls80j                                           0.333333       \n",
+       "e5mhgl5                                           0.666667       \n",
+       "e6w6fah                                           0.000000       \n",
+       "...                                                    ...       \n",
+       "e65ca8k                                           0.777778       \n",
+       "e6cdkpy                                           0.333333       \n",
+       "e5wc4tj                                           0.888889       \n",
+       "e6ua0sb                                           0.444444       \n",
+       "e5ua84v                                           0.555556       \n",
        "\n",
-       "         norm.2nd-largest[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                        0.125000   \n",
-       "e5ywqyk                                        0.400000   \n",
-       "e5qv9rj                                        0.333333   \n",
-       "e6jhojf                                        0.125000   \n",
-       "e6989ii                                        0.500000   \n",
-       "e69lgse                                        0.375000   \n",
-       "e5kwkg2                                        0.222222   \n",
-       "e6mehe7                                        0.250000   \n",
-       "e6m0hsd                                        0.250000   \n",
-       "e64r385                                        0.222222   \n",
-       "e5surbt                                        0.111111   \n",
-       "e58gxii                                        0.250000   \n",
-       "e64vc8y                                        0.111111   \n",
-       "e57504g                                        0.222222   \n",
-       "e5borjq                                        0.222222   \n",
-       "e64n9zv                                        0.250000   \n",
-       "e582ud3                                        0.222222   \n",
-       "e64i9cf                                        0.285714   \n",
-       "e6q9204                                        0.285714   \n",
-       "e5modd7                                        0.222222   \n",
-       "e5xhbyd                                        0.333333   \n",
-       "e5oaf7h                                        0.250000   \n",
-       "e6nir3u                                        0.500000   \n",
-       "e6c3xdn                                        0.111111   \n",
-       "e5d3zaa                                        0.285714   \n",
-       "e5gnjv9                                        0.111111   \n",
-       "e69gw2t                                        0.285714   \n",
-       "e5syrih                                        0.222222   \n",
-       "e5sa2yf                                        0.500000   \n",
-       "e6ai7z5                                        0.250000   \n",
-       "...                                                 ...   \n",
-       "e5smhzk                                        0.250000   \n",
-       "e5v91s0                                        0.222222   \n",
-       "e6n6di6                                        0.222222   \n",
-       "e6iqq30                                        0.111111   \n",
-       "e5bfad7                                        0.222222   \n",
-       "e6x5he5                                        0.125000   \n",
-       "e6l9uyf                                        0.222222   \n",
-       "e57hyr1                                        0.222222   \n",
-       "e5b8sj7                                        0.333333   \n",
-       "e6nlep7                                        0.000000   \n",
-       "e6ltazd                                        0.166667   \n",
-       "e57a6qq                                        0.333333   \n",
-       "e5qc7eb                                        0.428571   \n",
-       "e6hqt5y                                        0.444444   \n",
-       "e5ua84v                                        0.222222   \n",
-       "e65m7kq                                        0.333333   \n",
-       "e5ggtru                                        0.222222   \n",
-       "e5pmmig                                        0.285714   \n",
-       "e64l6vq                                        0.285714   \n",
-       "e6fjx0d                                        0.250000   \n",
-       "e5h3xyy                                        0.222222   \n",
-       "e589ri5                                        0.111111   \n",
-       "e5beuqa                                        0.222222   \n",
-       "e5lqoj1                                        0.125000   \n",
-       "e5kvch1                                        0.250000   \n",
-       "e6srvwm                                        0.222222   \n",
-       "e5o65mk                                        0.500000   \n",
-       "e647cm8                                        0.333333   \n",
-       "e58n526                                        0.000000   \n",
-       "e69r2kg                                        0.222222   \n",
+       "         prop-multiple[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.000000         \n",
+       "e5ytz1d                                           0.000000         \n",
+       "e6ls80j                                           0.250000         \n",
+       "e5mhgl5                                           0.333333         \n",
+       "e6w6fah                                           0.000000         \n",
+       "...                                                    ...         \n",
+       "e65ca8k                                           1.000000         \n",
+       "e6cdkpy                                           0.000000         \n",
+       "e5wc4tj                                           1.000000         \n",
+       "e6ua0sb                                           0.400000         \n",
+       "e5ua84v                                           0.333333         \n",
        "\n",
-       "         norm.2nd-largest[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667           \n",
-       "e5ywqyk                                           0.125000           \n",
-       "e5qv9rj                                           0.166667           \n",
-       "e6jhojf                                           0.125000           \n",
-       "e6989ii                                           0.142857           \n",
-       "e69lgse                                           0.166667           \n",
-       "e5kwkg2                                           0.166667           \n",
-       "e6mehe7                                           0.166667           \n",
-       "e6m0hsd                                           0.125000           \n",
-       "e64r385                                           0.285714           \n",
-       "e5surbt                                           0.250000           \n",
-       "e58gxii                                           0.285714           \n",
-       "e64vc8y                                           0.333333           \n",
-       "e57504g                                           0.285714           \n",
-       "e5borjq                                           0.285714           \n",
-       "e64n9zv                                           0.125000           \n",
-       "e582ud3                                           0.333333           \n",
-       "e64i9cf                                           0.200000           \n",
-       "e6q9204                                           0.250000           \n",
-       "e5modd7                                           0.250000           \n",
-       "e5xhbyd                                           0.250000           \n",
-       "e5oaf7h                                           0.250000           \n",
-       "e6nir3u                                           0.142857           \n",
-       "e6c3xdn                                           0.125000           \n",
-       "e5d3zaa                                           0.285714           \n",
-       "e5gnjv9                                           0.000000           \n",
-       "e69gw2t                                           0.285714           \n",
-       "e5syrih                                           0.250000           \n",
-       "e5sa2yf                                           0.125000           \n",
-       "e6ai7z5                                           0.166667           \n",
-       "...                                                    ...           \n",
-       "e5smhzk                                           0.142857           \n",
-       "e5v91s0                                           0.250000           \n",
-       "e6n6di6                                           0.250000           \n",
-       "e6iqq30                                           0.333333           \n",
-       "e5bfad7                                           0.333333           \n",
-       "e6x5he5                                           0.250000           \n",
-       "e6l9uyf                                           0.250000           \n",
-       "e57hyr1                                           0.200000           \n",
-       "e5b8sj7                                           0.333333           \n",
-       "e6nlep7                                                NaN           \n",
-       "e6ltazd                                           0.125000           \n",
-       "e57a6qq                                           0.250000           \n",
-       "e5qc7eb                                           0.285714           \n",
-       "e6hqt5y                                           0.200000           \n",
-       "e5ua84v                                           0.250000           \n",
-       "e65m7kq                                           0.200000           \n",
-       "e5ggtru                                           0.250000           \n",
-       "e5pmmig                                           0.125000           \n",
-       "e64l6vq                                           0.166667           \n",
-       "e6fjx0d                                           0.142857           \n",
-       "e5h3xyy                                           0.200000           \n",
-       "e589ri5                                           0.333333           \n",
-       "e5beuqa                                           0.142857           \n",
-       "e5lqoj1                                           0.250000           \n",
-       "e5kvch1                                           0.166667           \n",
-       "e6srvwm                                           0.333333           \n",
-       "e5o65mk                                           0.142857           \n",
-       "e647cm8                                           0.200000           \n",
-       "e58n526                                                NaN           \n",
-       "e69r2kg                                           0.285714           \n",
+       "         prop-multiple[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.166667        \n",
+       "e5ytz1d                                           0.666667        \n",
+       "e6ls80j                                           0.333333        \n",
+       "e5mhgl5                                           0.333333        \n",
+       "e6w6fah                                           0.000000        \n",
+       "...                                                    ...        \n",
+       "e65ca8k                                           0.000000        \n",
+       "e6cdkpy                                           0.666667        \n",
+       "e5wc4tj                                           0.000000        \n",
+       "e6ua0sb                                           0.250000        \n",
+       "e5ua84v                                           0.400000        \n",
        "\n",
-       "         norm.2nd-largest[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                        0.111111   \n",
-       "e5ywqyk                                        0.111111   \n",
-       "e5qv9rj                                        0.333333   \n",
-       "e6jhojf                                        0.111111   \n",
-       "e6989ii                                        0.125000   \n",
-       "e69lgse                                        0.333333   \n",
-       "e5kwkg2                                        0.222222   \n",
-       "e6mehe7                                        0.222222   \n",
-       "e6m0hsd                                        0.111111   \n",
-       "e64r385                                        0.222222   \n",
-       "e5surbt                                        0.111111   \n",
-       "e58gxii                                        0.222222   \n",
-       "e64vc8y                                        0.111111   \n",
-       "e57504g                                        0.222222   \n",
-       "e5borjq                                        0.222222   \n",
-       "e64n9zv                                        0.111111   \n",
-       "e582ud3                                        0.222222   \n",
-       "e64i9cf                                        0.222222   \n",
-       "e6q9204                                        0.222222   \n",
-       "e5modd7                                        0.222222   \n",
-       "e5xhbyd                                        0.222222   \n",
-       "e5oaf7h                                        0.222222   \n",
-       "e6nir3u                                        0.125000   \n",
-       "e6c3xdn                                        0.111111   \n",
-       "e5d3zaa                                        0.222222   \n",
-       "e5gnjv9                                        0.111111   \n",
-       "e69gw2t                                        0.222222   \n",
-       "e5syrih                                        0.222222   \n",
-       "e5sa2yf                                        0.111111   \n",
-       "e6ai7z5                                        0.111111   \n",
-       "...                                                 ...   \n",
-       "e5smhzk                                        0.111111   \n",
-       "e5v91s0                                        0.222222   \n",
-       "e6n6di6                                        0.222222   \n",
-       "e6iqq30                                        0.111111   \n",
-       "e5bfad7                                        0.222222   \n",
-       "e6x5he5                                        0.125000   \n",
-       "e6l9uyf                                        0.222222   \n",
-       "e57hyr1                                        0.222222   \n",
-       "e5b8sj7                                        0.333333   \n",
-       "e6nlep7                                        0.000000   \n",
-       "e6ltazd                                        0.111111   \n",
-       "e57a6qq                                        0.222222   \n",
-       "e5qc7eb                                        0.222222   \n",
-       "e6hqt5y                                        0.444444   \n",
-       "e5ua84v                                        0.222222   \n",
-       "e65m7kq                                        0.222222   \n",
-       "e5ggtru                                        0.222222   \n",
-       "e5pmmig                                        0.111111   \n",
-       "e64l6vq                                        0.222222   \n",
-       "e6fjx0d                                        0.111111   \n",
-       "e5h3xyy                                        0.222222   \n",
-       "e589ri5                                        0.111111   \n",
-       "e5beuqa                                        0.222222   \n",
-       "e5lqoj1                                        0.111111   \n",
-       "e5kvch1                                        0.111111   \n",
-       "e6srvwm                                        0.222222   \n",
-       "e5o65mk                                        0.125000   \n",
-       "e647cm8                                        0.333333   \n",
-       "e58n526                                        0.000000   \n",
-       "e69r2kg                                        0.222222   \n",
+       "         entropy[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.386294   \n",
+       "e5ytz1d                                           1.791759   \n",
+       "e6ls80j                                           1.332179   \n",
+       "e5mhgl5                                           1.732868   \n",
+       "e6w6fah                                                NaN   \n",
+       "...                                                    ...   \n",
+       "e65ca8k                                           0.000000   \n",
+       "e6cdkpy                                           1.609438   \n",
+       "e5wc4tj                                           0.693147   \n",
+       "e6ua0sb                                           1.549826   \n",
+       "e5ua84v                                           1.732868   \n",
        "\n",
-       "         norm.2nd-largest[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667           \n",
-       "e5ywqyk                                           0.125000           \n",
-       "e5qv9rj                                           0.166667           \n",
-       "e6jhojf                                           0.125000           \n",
-       "e6989ii                                           0.125000           \n",
-       "e69lgse                                           0.166667           \n",
-       "e5kwkg2                                           0.166667           \n",
-       "e6mehe7                                           0.166667           \n",
-       "e6m0hsd                                           0.125000           \n",
-       "e64r385                                           0.285714           \n",
-       "e5surbt                                           0.250000           \n",
-       "e58gxii                                           0.285714           \n",
-       "e64vc8y                                           0.333333           \n",
-       "e57504g                                           0.285714           \n",
-       "e5borjq                                           0.285714           \n",
-       "e64n9zv                                           0.125000           \n",
-       "e582ud3                                           0.333333           \n",
-       "e64i9cf                                           0.200000           \n",
-       "e6q9204                                           0.250000           \n",
-       "e5modd7                                           0.250000           \n",
-       "e5xhbyd                                           0.250000           \n",
-       "e5oaf7h                                           0.250000           \n",
-       "e6nir3u                                           0.125000           \n",
-       "e6c3xdn                                           0.125000           \n",
-       "e5d3zaa                                           0.285714           \n",
-       "e5gnjv9                                           0.000000           \n",
-       "e69gw2t                                           0.285714           \n",
-       "e5syrih                                           0.250000           \n",
-       "e5sa2yf                                           0.125000           \n",
-       "e6ai7z5                                           0.166667           \n",
-       "...                                                    ...           \n",
-       "e5smhzk                                           0.142857           \n",
-       "e5v91s0                                           0.250000           \n",
-       "e6n6di6                                           0.250000           \n",
-       "e6iqq30                                           0.333333           \n",
-       "e5bfad7                                           0.333333           \n",
-       "e6x5he5                                           0.200000           \n",
-       "e6l9uyf                                           0.250000           \n",
-       "e57hyr1                                           0.200000           \n",
-       "e5b8sj7                                           0.333333           \n",
-       "e6nlep7                                                NaN           \n",
-       "e6ltazd                                           0.125000           \n",
-       "e57a6qq                                           0.250000           \n",
-       "e5qc7eb                                           0.285714           \n",
-       "e6hqt5y                                           0.200000           \n",
-       "e5ua84v                                           0.250000           \n",
-       "e65m7kq                                           0.200000           \n",
-       "e5ggtru                                           0.250000           \n",
-       "e5pmmig                                           0.125000           \n",
-       "e64l6vq                                           0.166667           \n",
-       "e6fjx0d                                           0.142857           \n",
-       "e5h3xyy                                           0.200000           \n",
-       "e589ri5                                           0.333333           \n",
-       "e5beuqa                                           0.142857           \n",
-       "e5lqoj1                                           0.250000           \n",
-       "e5kvch1                                           0.166667           \n",
-       "e6srvwm                                           0.333333           \n",
-       "e5o65mk                                           0.142857           \n",
-       "e647cm8                                           0.200000           \n",
-       "e58n526                                                NaN           \n",
-       "e69r2kg                                           0.285714           \n",
+       "         entropy[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                          1.667462   \n",
+       "e5ytz1d                                          1.011404   \n",
+       "e6ls80j                                          0.950271   \n",
+       "e5mhgl5                                          1.732868   \n",
+       "e6w6fah                                               NaN   \n",
+       "...                                                   ...   \n",
+       "e65ca8k                                          1.945910   \n",
+       "e6cdkpy                                          1.054920   \n",
+       "e5wc4tj                                          2.079442   \n",
+       "e6ua0sb                                          1.153742   \n",
+       "e5ua84v                                          1.494175   \n",
        "\n",
-       "         norm.2nd-largest[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                        0.111111   \n",
-       "e5ywqyk                                        0.111111   \n",
-       "e5qv9rj                                        0.333333   \n",
-       "e6jhojf                                        0.111111   \n",
-       "e6989ii                                        0.111111   \n",
-       "e69lgse                                        0.333333   \n",
-       "e5kwkg2                                        0.222222   \n",
-       "e6mehe7                                        0.222222   \n",
-       "e6m0hsd                                        0.111111   \n",
-       "e64r385                                        0.222222   \n",
-       "e5surbt                                        0.111111   \n",
-       "e58gxii                                        0.222222   \n",
-       "e64vc8y                                        0.111111   \n",
-       "e57504g                                        0.222222   \n",
-       "e5borjq                                        0.222222   \n",
-       "e64n9zv                                        0.111111   \n",
-       "e582ud3                                        0.222222   \n",
-       "e64i9cf                                        0.222222   \n",
-       "e6q9204                                        0.222222   \n",
-       "e5modd7                                        0.222222   \n",
-       "e5xhbyd                                        0.222222   \n",
-       "e5oaf7h                                        0.222222   \n",
-       "e6nir3u                                        0.111111   \n",
-       "e6c3xdn                                        0.111111   \n",
-       "e5d3zaa                                        0.222222   \n",
-       "e5gnjv9                                        0.111111   \n",
-       "e69gw2t                                        0.222222   \n",
-       "e5syrih                                        0.222222   \n",
-       "e5sa2yf                                        0.111111   \n",
-       "e6ai7z5                                        0.111111   \n",
-       "...                                                 ...   \n",
-       "e5smhzk                                        0.111111   \n",
-       "e5v91s0                                        0.222222   \n",
-       "e6n6di6                                        0.222222   \n",
-       "e6iqq30                                        0.111111   \n",
-       "e5bfad7                                        0.222222   \n",
-       "e6x5he5                                        0.222222   \n",
-       "e6l9uyf                                        0.222222   \n",
-       "e57hyr1                                        0.222222   \n",
-       "e5b8sj7                                        0.333333   \n",
-       "e6nlep7                                        0.000000   \n",
-       "e6ltazd                                        0.111111   \n",
-       "e57a6qq                                        0.222222   \n",
-       "e5qc7eb                                        0.222222   \n",
-       "e6hqt5y                                        0.444444   \n",
-       "e5ua84v                                        0.222222   \n",
-       "e65m7kq                                        0.222222   \n",
-       "e5ggtru                                        0.222222   \n",
-       "e5pmmig                                        0.111111   \n",
-       "e64l6vq                                        0.222222   \n",
-       "e6fjx0d                                        0.111111   \n",
-       "e5h3xyy                                        0.222222   \n",
-       "e589ri5                                        0.111111   \n",
-       "e5beuqa                                        0.222222   \n",
-       "e5lqoj1                                        0.111111   \n",
-       "e5kvch1                                        0.111111   \n",
-       "e6srvwm                                        0.222222   \n",
-       "e5o65mk                                        0.111111   \n",
-       "e647cm8                                        0.333333   \n",
-       "e58n526                                        0.000000   \n",
-       "e69r2kg                                        0.222222   \n",
+       "         2nd-largest / max[outdegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0             \n",
+       "e5ytz1d                                                1.0             \n",
+       "e6ls80j                                                0.5             \n",
+       "e5mhgl5                                                1.0             \n",
+       "e6w6fah                                                NaN             \n",
+       "...                                                    ...             \n",
+       "e65ca8k                                                0.0             \n",
+       "e6cdkpy                                                1.0             \n",
+       "e5wc4tj                                                1.0             \n",
+       "e6ua0sb                                                1.0             \n",
+       "e5ua84v                                                1.0             \n",
        "\n",
-       "         norm.2nd-largest[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667            \n",
-       "e5ywqyk                                           0.250000            \n",
-       "e5qv9rj                                           0.166667            \n",
-       "e6jhojf                                           0.142857            \n",
-       "e6989ii                                           0.500000            \n",
-       "e69lgse                                           0.166667            \n",
-       "e5kwkg2                                           0.166667            \n",
-       "e6mehe7                                           0.200000            \n",
-       "e6m0hsd                                           0.250000            \n",
-       "e64r385                                           0.142857            \n",
-       "e5surbt                                           0.250000            \n",
-       "e58gxii                                           0.142857            \n",
-       "e64vc8y                                           0.333333            \n",
-       "e57504g                                           0.142857            \n",
-       "e5borjq                                           0.142857            \n",
-       "e64n9zv                                           0.250000            \n",
-       "e582ud3                                           0.333333            \n",
-       "e64i9cf                                           0.250000            \n",
-       "e6q9204                                           0.166667            \n",
-       "e5modd7                                           0.125000            \n",
-       "e5xhbyd                                           0.333333            \n",
-       "e5oaf7h                                           0.250000            \n",
-       "e6nir3u                                           0.500000            \n",
-       "e6c3xdn                                           0.125000            \n",
-       "e5d3zaa                                           0.200000            \n",
-       "e5gnjv9                                           0.000000            \n",
-       "e69gw2t                                           0.200000            \n",
-       "e5syrih                                           0.125000            \n",
-       "e5sa2yf                                           0.500000            \n",
-       "e6ai7z5                                           0.166667            \n",
+       "         2nd-largest / max[indegree over C->c mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.333333            \n",
+       "e5ytz1d                                           0.666667            \n",
+       "e6ls80j                                           0.333333            \n",
+       "e5mhgl5                                           1.000000            \n",
+       "e6w6fah                                                NaN            \n",
        "...                                                    ...            \n",
-       "e5smhzk                                           0.333333            \n",
-       "e5v91s0                                           0.250000            \n",
-       "e6n6di6                                           0.125000            \n",
-       "e6iqq30                                           0.333333            \n",
-       "e5bfad7                                           0.166667            \n",
-       "e6x5he5                                           0.000000            \n",
-       "e6l9uyf                                           0.250000            \n",
-       "e57hyr1                                           0.200000            \n",
-       "e5b8sj7                                           0.166667            \n",
-       "e6nlep7                                                NaN            \n",
-       "e6ltazd                                           0.200000            \n",
-       "e57a6qq                                           0.166667            \n",
-       "e5qc7eb                                           0.166667            \n",
-       "e6hqt5y                                           0.200000            \n",
-       "e5ua84v                                           0.250000            \n",
-       "e65m7kq                                           0.200000            \n",
-       "e5ggtru                                           0.125000            \n",
-       "e5pmmig                                           0.333333            \n",
-       "e64l6vq                                           0.200000            \n",
-       "e6fjx0d                                           0.500000            \n",
-       "e5h3xyy                                           0.200000            \n",
-       "e589ri5                                           0.333333            \n",
-       "e5beuqa                                           0.142857            \n",
-       "e5lqoj1                                           0.333333            \n",
-       "e5kvch1                                           0.200000            \n",
-       "e6srvwm                                           0.166667            \n",
-       "e5o65mk                                           0.500000            \n",
-       "e647cm8                                           0.200000            \n",
-       "e58n526                                                NaN            \n",
-       "e69r2kg                                           0.142857            \n",
+       "e65ca8k                                           1.000000            \n",
+       "e6cdkpy                                           1.000000            \n",
+       "e5wc4tj                                           1.000000            \n",
+       "e6ua0sb                                           0.250000            \n",
+       "e5ua84v                                           0.666667            \n",
        "\n",
-       "         norm.2nd-largest[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                         0.125000   \n",
-       "e5ywqyk                                         0.200000   \n",
-       "e5qv9rj                                         0.111111   \n",
-       "e6jhojf                                         0.125000   \n",
-       "e6989ii                                         0.500000   \n",
-       "e69lgse                                         0.125000   \n",
-       "e5kwkg2                                         0.111111   \n",
-       "e6mehe7                                         0.125000   \n",
-       "e6m0hsd                                         0.250000   \n",
-       "e64r385                                         0.222222   \n",
-       "e5surbt                                         0.111111   \n",
-       "e58gxii                                         0.125000   \n",
-       "e64vc8y                                         0.111111   \n",
-       "e57504g                                         0.222222   \n",
-       "e5borjq                                         0.111111   \n",
-       "e64n9zv                                         0.250000   \n",
-       "e582ud3                                         0.111111   \n",
-       "e64i9cf                                         0.142857   \n",
-       "e6q9204                                         0.142857   \n",
-       "e5modd7                                         0.111111   \n",
-       "e5xhbyd                                         0.333333   \n",
-       "e5oaf7h                                         0.250000   \n",
-       "e6nir3u                                         0.500000   \n",
-       "e6c3xdn                                         0.111111   \n",
-       "e5d3zaa                                         0.142857   \n",
-       "e5gnjv9                                         0.111111   \n",
-       "e69gw2t                                         0.285714   \n",
-       "e5syrih                                         0.222222   \n",
-       "e5sa2yf                                         0.500000   \n",
-       "e6ai7z5                                         0.125000   \n",
-       "...                                                  ...   \n",
-       "e5smhzk                                         0.250000   \n",
-       "e5v91s0                                         0.111111   \n",
-       "e6n6di6                                         0.111111   \n",
-       "e6iqq30                                         0.111111   \n",
-       "e5bfad7                                         0.111111   \n",
-       "e6x5he5                                         0.125000   \n",
-       "e6l9uyf                                         0.111111   \n",
-       "e57hyr1                                         0.222222   \n",
-       "e5b8sj7                                         0.111111   \n",
-       "e6nlep7                                         0.111111   \n",
-       "e6ltazd                                         0.166667   \n",
-       "e57a6qq                                         0.166667   \n",
-       "e5qc7eb                                         0.142857   \n",
-       "e6hqt5y                                         0.111111   \n",
-       "e5ua84v                                         0.222222   \n",
-       "e65m7kq                                         0.111111   \n",
-       "e5ggtru                                         0.111111   \n",
-       "e5pmmig                                         0.285714   \n",
-       "e64l6vq                                         0.142857   \n",
-       "e6fjx0d                                         0.250000   \n",
-       "e5h3xyy                                         0.111111   \n",
-       "e589ri5                                         0.111111   \n",
-       "e5beuqa                                         0.222222   \n",
-       "e5lqoj1                                         0.125000   \n",
-       "e5kvch1                                         0.250000   \n",
-       "e6srvwm                                         0.111111   \n",
-       "e5o65mk                                         0.500000   \n",
-       "e647cm8                                         0.111111   \n",
-       "e58n526                                         0.111111   \n",
-       "e69r2kg                                         0.111111   \n",
+       "         max[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                            2.0   \n",
+       "e5ytz1d                                            1.0   \n",
+       "e6ls80j                                            2.0   \n",
+       "e5mhgl5                                            2.0   \n",
+       "e6w6fah                                            0.0   \n",
+       "...                                                ...   \n",
+       "e65ca8k                                            1.0   \n",
+       "e6cdkpy                                            1.0   \n",
+       "e5wc4tj                                            1.0   \n",
+       "e6ua0sb                                            2.0   \n",
+       "e5ua84v                                            2.0   \n",
        "\n",
-       "         norm.2nd-largest[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667            \n",
-       "e5ywqyk                                           0.375000            \n",
-       "e5qv9rj                                           0.166667            \n",
-       "e6jhojf                                           0.250000            \n",
-       "e6989ii                                           0.428571            \n",
-       "e69lgse                                           0.166667            \n",
-       "e5kwkg2                                           0.166667            \n",
-       "e6mehe7                                           0.333333            \n",
-       "e6m0hsd                                           0.375000            \n",
-       "e64r385                                           0.142857            \n",
-       "e5surbt                                           0.250000            \n",
-       "e58gxii                                           0.142857            \n",
-       "e64vc8y                                           0.333333            \n",
-       "e57504g                                           0.142857            \n",
-       "e5borjq                                           0.142857            \n",
-       "e64n9zv                                           0.375000            \n",
-       "e582ud3                                           0.333333            \n",
-       "e64i9cf                                           0.200000            \n",
-       "e6q9204                                           0.250000            \n",
-       "e5modd7                                           0.125000            \n",
-       "e5xhbyd                                           0.250000            \n",
-       "e5oaf7h                                           0.375000            \n",
-       "e6nir3u                                           0.428571            \n",
-       "e6c3xdn                                           0.125000            \n",
-       "e5d3zaa                                           0.285714            \n",
-       "e5gnjv9                                           0.000000            \n",
-       "e69gw2t                                           0.285714            \n",
-       "e5syrih                                           0.125000            \n",
-       "e5sa2yf                                           0.500000            \n",
-       "e6ai7z5                                           0.166667            \n",
-       "...                                                    ...            \n",
-       "e5smhzk                                           0.428571            \n",
-       "e5v91s0                                           0.250000            \n",
-       "e6n6di6                                           0.125000            \n",
-       "e6iqq30                                           0.333333            \n",
-       "e5bfad7                                           0.166667            \n",
-       "e6x5he5                                           0.000000            \n",
-       "e6l9uyf                                           0.250000            \n",
-       "e57hyr1                                           0.200000            \n",
-       "e5b8sj7                                           0.166667            \n",
-       "e6nlep7                                                NaN            \n",
-       "e6ltazd                                           0.250000            \n",
-       "e57a6qq                                           0.250000            \n",
-       "e5qc7eb                                           0.142857            \n",
-       "e6hqt5y                                           0.200000            \n",
-       "e5ua84v                                           0.250000            \n",
-       "e65m7kq                                           0.200000            \n",
-       "e5ggtru                                           0.125000            \n",
-       "e5pmmig                                           0.250000            \n",
-       "e64l6vq                                           0.166667            \n",
-       "e6fjx0d                                           0.428571            \n",
-       "e5h3xyy                                           0.200000            \n",
-       "e589ri5                                           0.333333            \n",
-       "e5beuqa                                           0.142857            \n",
-       "e5lqoj1                                           0.500000            \n",
-       "e5kvch1                                           0.166667            \n",
-       "e6srvwm                                           0.166667            \n",
-       "e5o65mk                                           0.428571            \n",
-       "e647cm8                                           0.200000            \n",
-       "e58n526                                                NaN            \n",
-       "e69r2kg                                           0.142857            \n",
+       "         max[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           3.0   \n",
+       "e5ytz1d                                           3.0   \n",
+       "e6ls80j                                           3.0   \n",
+       "e5mhgl5                                           2.0   \n",
+       "e6w6fah                                           0.0   \n",
+       "...                                               ...   \n",
+       "e65ca8k                                           1.0   \n",
+       "e6cdkpy                                           2.0   \n",
+       "e5wc4tj                                           1.0   \n",
+       "e6ua0sb                                           4.0   \n",
+       "e5ua84v                                           4.0   \n",
        "\n",
-       "         norm.2nd-largest[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                         0.222222   \n",
-       "e5ywqyk                                         0.333333   \n",
-       "e5qv9rj                                         0.111111   \n",
-       "e6jhojf                                         0.222222   \n",
-       "e6989ii                                         0.500000   \n",
-       "e69lgse                                         0.222222   \n",
-       "e5kwkg2                                         0.111111   \n",
-       "e6mehe7                                         0.222222   \n",
-       "e6m0hsd                                         0.333333   \n",
-       "e64r385                                         0.222222   \n",
-       "e5surbt                                         0.111111   \n",
-       "e58gxii                                         0.222222   \n",
-       "e64vc8y                                         0.111111   \n",
-       "e57504g                                         0.222222   \n",
-       "e5borjq                                         0.111111   \n",
-       "e64n9zv                                         0.333333   \n",
-       "e582ud3                                         0.111111   \n",
-       "e64i9cf                                         0.222222   \n",
-       "e6q9204                                         0.222222   \n",
-       "e5modd7                                         0.111111   \n",
-       "e5xhbyd                                         0.333333   \n",
-       "e5oaf7h                                         0.333333   \n",
-       "e6nir3u                                         0.500000   \n",
-       "e6c3xdn                                         0.111111   \n",
-       "e5d3zaa                                         0.222222   \n",
-       "e5gnjv9                                         0.111111   \n",
-       "e69gw2t                                         0.333333   \n",
-       "e5syrih                                         0.222222   \n",
-       "e5sa2yf                                         0.444444   \n",
-       "e6ai7z5                                         0.111111   \n",
+       "         argmax[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                               1.0   \n",
+       "e5ytz1d                                               3.0   \n",
+       "e6ls80j                                               2.0   \n",
+       "e5mhgl5                                               3.0   \n",
+       "e6w6fah                                               0.0   \n",
+       "...                                                   ...   \n",
+       "e65ca8k                                               1.0   \n",
+       "e6cdkpy                                               2.0   \n",
+       "e5wc4tj                                               0.0   \n",
+       "e6ua0sb                                               2.0   \n",
+       "e5ua84v                                               0.0   \n",
+       "\n",
+       "         argmax[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                              0.0   \n",
+       "e5ytz1d                                              1.0   \n",
+       "e6ls80j                                              1.0   \n",
+       "e5mhgl5                                              0.0   \n",
+       "e6w6fah                                              0.0   \n",
        "...                                                  ...   \n",
-       "e5smhzk                                         0.444444   \n",
-       "e5v91s0                                         0.111111   \n",
-       "e6n6di6                                         0.111111   \n",
-       "e6iqq30                                         0.111111   \n",
-       "e5bfad7                                         0.111111   \n",
-       "e6x5he5                                         0.125000   \n",
-       "e6l9uyf                                         0.111111   \n",
-       "e57hyr1                                         0.222222   \n",
-       "e5b8sj7                                         0.111111   \n",
-       "e6nlep7                                         0.111111   \n",
-       "e6ltazd                                         0.333333   \n",
-       "e57a6qq                                         0.333333   \n",
-       "e5qc7eb                                         0.222222   \n",
-       "e6hqt5y                                         0.111111   \n",
-       "e5ua84v                                         0.222222   \n",
-       "e65m7kq                                         0.111111   \n",
-       "e5ggtru                                         0.111111   \n",
-       "e5pmmig                                         0.333333   \n",
-       "e64l6vq                                         0.222222   \n",
-       "e6fjx0d                                         0.444444   \n",
-       "e5h3xyy                                         0.111111   \n",
-       "e589ri5                                         0.111111   \n",
-       "e5beuqa                                         0.222222   \n",
-       "e5lqoj1                                         0.222222   \n",
-       "e5kvch1                                         0.222222   \n",
-       "e6srvwm                                         0.111111   \n",
-       "e5o65mk                                         0.500000   \n",
-       "e647cm8                                         0.111111   \n",
-       "e58n526                                         0.111111   \n",
-       "e69r2kg                                         0.111111   \n",
+       "e65ca8k                                              1.0   \n",
+       "e6cdkpy                                              0.0   \n",
+       "e5wc4tj                                              0.0   \n",
+       "e6ua0sb                                              1.0   \n",
+       "e5ua84v                                              0.0   \n",
+       "\n",
+       "         norm.max[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.285714    \n",
+       "e5ytz1d                                           0.166667    \n",
+       "e6ls80j                                           0.400000    \n",
+       "e5mhgl5                                           0.285714    \n",
+       "e6w6fah                                           0.000000    \n",
+       "...                                                    ...    \n",
+       "e65ca8k                                           1.000000    \n",
+       "e6cdkpy                                           0.200000    \n",
+       "e5wc4tj                                           0.500000    \n",
+       "e6ua0sb                                           0.285714    \n",
+       "e5ua84v                                           0.250000    \n",
        "\n",
        "         norm.max[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.500000   \n",
-       "e5ywqyk                                           0.500000   \n",
-       "e5qv9rj                                           0.500000   \n",
-       "e6jhojf                                           0.428571   \n",
-       "e6989ii                                           0.500000   \n",
-       "e69lgse                                           0.500000   \n",
-       "e5kwkg2                                           0.333333   \n",
-       "e6mehe7                                           0.400000   \n",
-       "e6m0hsd                                           0.500000   \n",
-       "e64r385                                           0.285714   \n",
-       "e5surbt                                           0.250000   \n",
-       "e58gxii                                           0.428571   \n",
-       "e64vc8y                                           0.333333   \n",
-       "e57504g                                           0.285714   \n",
-       "e5borjq                                           0.428571   \n",
-       "e64n9zv                                           0.500000   \n",
-       "e582ud3                                           0.666667   \n",
-       "e64i9cf                                           0.500000   \n",
-       "e6q9204                                           0.500000   \n",
-       "e5modd7                                           0.500000   \n",
-       "e5xhbyd                                           0.333333   \n",
-       "e5oaf7h                                           0.750000   \n",
-       "e6nir3u                                           0.500000   \n",
-       "e6c3xdn                                           0.250000   \n",
-       "e5d3zaa                                           0.400000   \n",
-       "e5gnjv9                                           1.000000   \n",
-       "e69gw2t                                           0.400000   \n",
-       "e5syrih                                           0.500000   \n",
-       "e5sa2yf                                           0.500000   \n",
-       "e6ai7z5                                           0.333333   \n",
+       "e5hm9mp                                           0.428571   \n",
+       "e5ytz1d                                           0.500000   \n",
+       "e6ls80j                                           0.600000   \n",
+       "e5mhgl5                                           0.285714   \n",
+       "e6w6fah                                           0.000000   \n",
        "...                                                    ...   \n",
-       "e5smhzk                                           0.333333   \n",
-       "e5v91s0                                           0.500000   \n",
-       "e6n6di6                                           0.500000   \n",
-       "e6iqq30                                           0.333333   \n",
-       "e5bfad7                                           0.333333   \n",
-       "e6x5he5                                           0.250000   \n",
-       "e6l9uyf                                           0.500000   \n",
-       "e57hyr1                                           0.400000   \n",
-       "e5b8sj7                                           0.666667   \n",
-       "e6nlep7                                           0.000000   \n",
-       "e6ltazd                                           0.800000   \n",
-       "e57a6qq                                           0.500000   \n",
-       "e5qc7eb                                           0.500000   \n",
-       "e6hqt5y                                           0.800000   \n",
+       "e65ca8k                                           1.000000   \n",
+       "e6cdkpy                                           0.400000   \n",
+       "e5wc4tj                                           0.500000   \n",
+       "e6ua0sb                                           0.571429   \n",
        "e5ua84v                                           0.500000   \n",
-       "e65m7kq                                           0.600000   \n",
-       "e5ggtru                                           0.625000   \n",
-       "e5pmmig                                           0.333333   \n",
-       "e64l6vq                                           0.400000   \n",
-       "e6fjx0d                                           0.500000   \n",
-       "e5h3xyy                                           0.400000   \n",
-       "e589ri5                                           0.333333   \n",
-       "e5beuqa                                           0.571429   \n",
-       "e5lqoj1                                           0.333333   \n",
-       "e5kvch1                                           0.400000   \n",
-       "e6srvwm                                           0.333333   \n",
-       "e5o65mk                                           0.500000   \n",
-       "e647cm8                                           0.600000   \n",
-       "e58n526                                           0.000000   \n",
-       "e69r2kg                                           0.428571   \n",
-       "\n",
-       "         norm.max[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                0.625000   \n",
-       "e5ywqyk                                0.400000   \n",
-       "e5qv9rj                                0.333333   \n",
-       "e6jhojf                                0.500000   \n",
-       "e6989ii                                0.500000   \n",
-       "e69lgse                                0.375000   \n",
-       "e5kwkg2                                0.333333   \n",
-       "e6mehe7                                0.500000   \n",
-       "e6m0hsd                                0.500000   \n",
-       "e64r385                                0.222222   \n",
-       "e5surbt                                0.555556   \n",
-       "e58gxii                                0.500000   \n",
-       "e64vc8y                                0.666667   \n",
-       "e57504g                                0.222222   \n",
-       "e5borjq                                0.333333   \n",
-       "e64n9zv                                0.500000   \n",
-       "e582ud3                                0.666667   \n",
-       "e64i9cf                                0.571429   \n",
-       "e6q9204                                0.428571   \n",
-       "e5modd7                                0.444444   \n",
-       "e5xhbyd                                0.333333   \n",
-       "e5oaf7h                                0.750000   \n",
-       "e6nir3u                                0.500000   \n",
-       "e6c3xdn                                0.222222   \n",
-       "e5d3zaa                                0.285714   \n",
-       "e5gnjv9                                0.888889   \n",
-       "e69gw2t                                0.285714   \n",
-       "e5syrih                                0.444444   \n",
-       "e5sa2yf                                0.500000   \n",
-       "e6ai7z5                                0.375000   \n",
-       "...                                         ...   \n",
-       "e5smhzk                                0.500000   \n",
-       "e5v91s0                                0.555556   \n",
-       "e6n6di6                                0.444444   \n",
-       "e6iqq30                                0.666667   \n",
-       "e5bfad7                                0.444444   \n",
-       "e6x5he5                                0.500000   \n",
-       "e6l9uyf                                0.555556   \n",
-       "e57hyr1                                0.444444   \n",
-       "e5b8sj7                                0.444444   \n",
-       "e6nlep7                                1.000000   \n",
-       "e6ltazd                                0.666667   \n",
-       "e57a6qq                                0.500000   \n",
-       "e5qc7eb                                0.428571   \n",
-       "e6hqt5y                                0.444444   \n",
-       "e5ua84v                                0.444444   \n",
-       "e65m7kq                                0.444444   \n",
-       "e5ggtru                                0.555556   \n",
-       "e5pmmig                                0.285714   \n",
-       "e64l6vq                                0.428571   \n",
-       "e6fjx0d                                0.500000   \n",
-       "e5h3xyy                                0.444444   \n",
-       "e589ri5                                0.666667   \n",
-       "e5beuqa                                0.444444   \n",
-       "e5lqoj1                                0.625000   \n",
-       "e5kvch1                                0.375000   \n",
-       "e6srvwm                                0.333333   \n",
-       "e5o65mk                                0.500000   \n",
-       "e647cm8                                0.444444   \n",
-       "e58n526                                1.000000   \n",
-       "e69r2kg                                0.333333   \n",
-       "\n",
-       "         norm.max[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667   \n",
-       "e5ywqyk                                           0.250000   \n",
-       "e5qv9rj                                           0.500000   \n",
-       "e6jhojf                                           0.250000   \n",
-       "e6989ii                                           0.142857   \n",
-       "e69lgse                                           0.500000   \n",
-       "e5kwkg2                                           0.333333   \n",
-       "e6mehe7                                           0.333333   \n",
-       "e6m0hsd                                           0.250000   \n",
-       "e64r385                                           0.285714   \n",
-       "e5surbt                                           0.250000   \n",
-       "e58gxii                                           0.285714   \n",
-       "e64vc8y                                           0.333333   \n",
-       "e57504g                                           0.285714   \n",
-       "e5borjq                                           0.428571   \n",
-       "e64n9zv                                           0.250000   \n",
-       "e582ud3                                           0.666667   \n",
-       "e64i9cf                                           0.400000   \n",
-       "e6q9204                                           0.250000   \n",
-       "e5modd7                                           0.500000   \n",
-       "e5xhbyd                                           0.250000   \n",
-       "e5oaf7h                                           0.250000   \n",
-       "e6nir3u                                           0.142857   \n",
-       "e6c3xdn                                           0.250000   \n",
-       "e5d3zaa                                           0.285714   \n",
-       "e5gnjv9                                           1.000000   \n",
-       "e69gw2t                                           0.285714   \n",
-       "e5syrih                                           0.375000   \n",
-       "e5sa2yf                                           0.125000   \n",
-       "e6ai7z5                                           0.166667   \n",
-       "...                                                    ...   \n",
-       "e5smhzk                                           0.142857   \n",
-       "e5v91s0                                           0.500000   \n",
-       "e6n6di6                                           0.375000   \n",
-       "e6iqq30                                           0.333333   \n",
-       "e5bfad7                                           0.333333   \n",
-       "e6x5he5                                           0.250000   \n",
-       "e6l9uyf                                           0.500000   \n",
-       "e57hyr1                                           0.400000   \n",
-       "e5b8sj7                                           0.500000   \n",
-       "e6nlep7                                           0.000000   \n",
-       "e6ltazd                                           0.500000   \n",
-       "e57a6qq                                           0.250000   \n",
-       "e5qc7eb                                           0.428571   \n",
-       "e6hqt5y                                           0.800000   \n",
-       "e5ua84v                                           0.375000   \n",
-       "e65m7kq                                           0.400000   \n",
-       "e5ggtru                                           0.500000   \n",
-       "e5pmmig                                           0.250000   \n",
-       "e64l6vq                                           0.333333   \n",
-       "e6fjx0d                                           0.142857   \n",
-       "e5h3xyy                                           0.400000   \n",
-       "e589ri5                                           0.333333   \n",
-       "e5beuqa                                           0.428571   \n",
-       "e5lqoj1                                           0.250000   \n",
-       "e5kvch1                                           0.166667   \n",
-       "e6srvwm                                           0.333333   \n",
-       "e5o65mk                                           0.142857   \n",
-       "e647cm8                                           0.600000   \n",
-       "e58n526                                           0.000000   \n",
-       "e69r2kg                                           0.285714   \n",
-       "\n",
-       "         norm.max[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                0.333333   \n",
-       "e5ywqyk                                0.222222   \n",
-       "e5qv9rj                                0.333333   \n",
-       "e6jhojf                                0.222222   \n",
-       "e6989ii                                0.125000   \n",
-       "e69lgse                                0.333333   \n",
-       "e5kwkg2                                0.333333   \n",
-       "e6mehe7                                0.333333   \n",
-       "e6m0hsd                                0.222222   \n",
-       "e64r385                                0.222222   \n",
-       "e5surbt                                0.555556   \n",
-       "e58gxii                                0.222222   \n",
-       "e64vc8y                                0.666667   \n",
-       "e57504g                                0.222222   \n",
-       "e5borjq                                0.333333   \n",
-       "e64n9zv                                0.222222   \n",
-       "e582ud3                                0.666667   \n",
-       "e64i9cf                                0.444444   \n",
-       "e6q9204                                0.222222   \n",
-       "e5modd7                                0.444444   \n",
-       "e5xhbyd                                0.222222   \n",
-       "e5oaf7h                                0.222222   \n",
-       "e6nir3u                                0.125000   \n",
-       "e6c3xdn                                0.222222   \n",
-       "e5d3zaa                                0.222222   \n",
-       "e5gnjv9                                0.888889   \n",
-       "e69gw2t                                0.222222   \n",
-       "e5syrih                                0.333333   \n",
-       "e5sa2yf                                0.111111   \n",
-       "e6ai7z5                                0.333333   \n",
-       "...                                         ...   \n",
-       "e5smhzk                                0.222222   \n",
-       "e5v91s0                                0.555556   \n",
-       "e6n6di6                                0.333333   \n",
-       "e6iqq30                                0.666667   \n",
-       "e5bfad7                                0.333333   \n",
-       "e6x5he5                                0.500000   \n",
-       "e6l9uyf                                0.555556   \n",
-       "e57hyr1                                0.444444   \n",
-       "e5b8sj7                                0.333333   \n",
-       "e6nlep7                                1.000000   \n",
-       "e6ltazd                                0.444444   \n",
-       "e57a6qq                                0.222222   \n",
-       "e5qc7eb                                0.333333   \n",
-       "e6hqt5y                                0.444444   \n",
-       "e5ua84v                                0.333333   \n",
-       "e65m7kq                                0.444444   \n",
-       "e5ggtru                                0.444444   \n",
-       "e5pmmig                                0.222222   \n",
-       "e64l6vq                                0.333333   \n",
-       "e6fjx0d                                0.222222   \n",
-       "e5h3xyy                                0.444444   \n",
-       "e589ri5                                0.666667   \n",
-       "e5beuqa                                0.333333   \n",
-       "e5lqoj1                                0.555556   \n",
-       "e5kvch1                                0.333333   \n",
-       "e6srvwm                                0.333333   \n",
-       "e5o65mk                                0.125000   \n",
-       "e647cm8                                0.444444   \n",
-       "e58n526                                1.000000   \n",
-       "e69r2kg                                0.222222   \n",
        "\n",
-       "         norm.max[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.166667   \n",
-       "e5ywqyk                                           0.250000   \n",
-       "e5qv9rj                                           0.500000   \n",
-       "e6jhojf                                           0.250000   \n",
-       "e6989ii                                           0.250000   \n",
-       "e69lgse                                           0.500000   \n",
-       "e5kwkg2                                           0.333333   \n",
-       "e6mehe7                                           0.333333   \n",
-       "e6m0hsd                                           0.250000   \n",
-       "e64r385                                           0.285714   \n",
-       "e5surbt                                           0.250000   \n",
-       "e58gxii                                           0.285714   \n",
-       "e64vc8y                                           0.333333   \n",
-       "e57504g                                           0.285714   \n",
-       "e5borjq                                           0.428571   \n",
-       "e64n9zv                                           0.250000   \n",
-       "e582ud3                                           0.666667   \n",
-       "e64i9cf                                           0.400000   \n",
-       "e6q9204                                           0.250000   \n",
-       "e5modd7                                           0.500000   \n",
-       "e5xhbyd                                           0.250000   \n",
-       "e5oaf7h                                           0.250000   \n",
-       "e6nir3u                                           0.250000   \n",
-       "e6c3xdn                                           0.250000   \n",
-       "e5d3zaa                                           0.285714   \n",
-       "e5gnjv9                                           1.000000   \n",
-       "e69gw2t                                           0.285714   \n",
-       "e5syrih                                           0.375000   \n",
-       "e5sa2yf                                           0.125000   \n",
-       "e6ai7z5                                           0.166667   \n",
-       "...                                                    ...   \n",
-       "e5smhzk                                           0.142857   \n",
-       "e5v91s0                                           0.500000   \n",
-       "e6n6di6                                           0.375000   \n",
-       "e6iqq30                                           0.333333   \n",
-       "e5bfad7                                           0.333333   \n",
-       "e6x5he5                                           0.400000   \n",
-       "e6l9uyf                                           0.500000   \n",
-       "e57hyr1                                           0.400000   \n",
-       "e5b8sj7                                           0.500000   \n",
-       "e6nlep7                                           0.000000   \n",
-       "e6ltazd                                           0.500000   \n",
-       "e57a6qq                                           0.250000   \n",
-       "e5qc7eb                                           0.428571   \n",
-       "e6hqt5y                                           0.800000   \n",
-       "e5ua84v                                           0.375000   \n",
-       "e65m7kq                                           0.400000   \n",
-       "e5ggtru                                           0.500000   \n",
-       "e5pmmig                                           0.250000   \n",
-       "e64l6vq                                           0.333333   \n",
-       "e6fjx0d                                           0.142857   \n",
-       "e5h3xyy                                           0.400000   \n",
-       "e589ri5                                           0.333333   \n",
-       "e5beuqa                                           0.428571   \n",
-       "e5lqoj1                                           0.250000   \n",
-       "e5kvch1                                           0.166667   \n",
-       "e6srvwm                                           0.333333   \n",
-       "e5o65mk                                           0.142857   \n",
-       "e647cm8                                           0.600000   \n",
-       "e58n526                                           0.000000   \n",
-       "e69r2kg                                           0.285714   \n",
+       "         2nd-largest[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                2.0       \n",
+       "e5ytz1d                                                1.0       \n",
+       "e6ls80j                                                1.0       \n",
+       "e5mhgl5                                                1.0       \n",
+       "e6w6fah                                                0.0       \n",
+       "...                                                    ...       \n",
+       "e65ca8k                                                0.0       \n",
+       "e6cdkpy                                                1.0       \n",
+       "e5wc4tj                                                1.0       \n",
+       "e6ua0sb                                                2.0       \n",
+       "e5ua84v                                                2.0       \n",
        "\n",
-       "         norm.max[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                0.333333   \n",
-       "e5ywqyk                                0.222222   \n",
-       "e5qv9rj                                0.333333   \n",
-       "e6jhojf                                0.222222   \n",
-       "e6989ii                                0.222222   \n",
-       "e69lgse                                0.333333   \n",
-       "e5kwkg2                                0.333333   \n",
-       "e6mehe7                                0.333333   \n",
-       "e6m0hsd                                0.222222   \n",
-       "e64r385                                0.222222   \n",
-       "e5surbt                                0.555556   \n",
-       "e58gxii                                0.222222   \n",
-       "e64vc8y                                0.666667   \n",
-       "e57504g                                0.222222   \n",
-       "e5borjq                                0.333333   \n",
-       "e64n9zv                                0.222222   \n",
-       "e582ud3                                0.666667   \n",
-       "e64i9cf                                0.444444   \n",
-       "e6q9204                                0.222222   \n",
-       "e5modd7                                0.444444   \n",
-       "e5xhbyd                                0.222222   \n",
-       "e5oaf7h                                0.222222   \n",
-       "e6nir3u                                0.222222   \n",
-       "e6c3xdn                                0.222222   \n",
-       "e5d3zaa                                0.222222   \n",
-       "e5gnjv9                                0.888889   \n",
-       "e69gw2t                                0.222222   \n",
-       "e5syrih                                0.333333   \n",
-       "e5sa2yf                                0.111111   \n",
-       "e6ai7z5                                0.333333   \n",
-       "...                                         ...   \n",
-       "e5smhzk                                0.222222   \n",
-       "e5v91s0                                0.555556   \n",
-       "e6n6di6                                0.333333   \n",
-       "e6iqq30                                0.666667   \n",
-       "e5bfad7                                0.333333   \n",
-       "e6x5he5                                0.444444   \n",
-       "e6l9uyf                                0.555556   \n",
-       "e57hyr1                                0.444444   \n",
-       "e5b8sj7                                0.333333   \n",
-       "e6nlep7                                1.000000   \n",
-       "e6ltazd                                0.444444   \n",
-       "e57a6qq                                0.222222   \n",
-       "e5qc7eb                                0.333333   \n",
-       "e6hqt5y                                0.444444   \n",
-       "e5ua84v                                0.333333   \n",
-       "e65m7kq                                0.444444   \n",
-       "e5ggtru                                0.444444   \n",
-       "e5pmmig                                0.222222   \n",
-       "e64l6vq                                0.333333   \n",
-       "e6fjx0d                                0.222222   \n",
-       "e5h3xyy                                0.444444   \n",
-       "e589ri5                                0.666667   \n",
-       "e5beuqa                                0.333333   \n",
-       "e5lqoj1                                0.555556   \n",
-       "e5kvch1                                0.333333   \n",
-       "e6srvwm                                0.333333   \n",
-       "e5o65mk                                0.222222   \n",
-       "e647cm8                                0.444444   \n",
-       "e58n526                                1.000000   \n",
-       "e69r2kg                                0.222222   \n",
+       "         2nd-largest[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0      \n",
+       "e5ytz1d                                                2.0      \n",
+       "e6ls80j                                                1.0      \n",
+       "e5mhgl5                                                2.0      \n",
+       "e6w6fah                                                0.0      \n",
+       "...                                                    ...      \n",
+       "e65ca8k                                                0.0      \n",
+       "e6cdkpy                                                2.0      \n",
+       "e5wc4tj                                                1.0      \n",
+       "e6ua0sb                                                1.0      \n",
+       "e5ua84v                                                2.0      \n",
        "\n",
-       "         norm.max[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.500000    \n",
-       "e5ywqyk                                           0.500000    \n",
-       "e5qv9rj                                           0.166667    \n",
-       "e6jhojf                                           0.571429    \n",
-       "e6989ii                                           0.500000    \n",
-       "e69lgse                                           0.333333    \n",
-       "e5kwkg2                                           0.166667    \n",
-       "e6mehe7                                           0.600000    \n",
-       "e6m0hsd                                           0.500000    \n",
-       "e64r385                                           0.285714    \n",
-       "e5surbt                                           0.250000    \n",
-       "e58gxii                                           0.428571    \n",
-       "e64vc8y                                           0.333333    \n",
-       "e57504g                                           0.285714    \n",
-       "e5borjq                                           0.142857    \n",
-       "e64n9zv                                           0.500000    \n",
-       "e582ud3                                           0.333333    \n",
-       "e64i9cf                                           0.500000    \n",
-       "e6q9204                                           0.333333    \n",
-       "e5modd7                                           0.125000    \n",
-       "e5xhbyd                                           0.333333    \n",
-       "e5oaf7h                                           0.500000    \n",
-       "e6nir3u                                           0.500000    \n",
-       "e6c3xdn                                           0.125000    \n",
-       "e5d3zaa                                           0.200000    \n",
-       "e5gnjv9                                           1.000000    \n",
-       "e69gw2t                                           0.400000    \n",
-       "e5syrih                                           0.250000    \n",
-       "e5sa2yf                                           0.500000    \n",
-       "e6ai7z5                                           0.666667    \n",
-       "...                                                    ...    \n",
-       "e5smhzk                                           0.666667    \n",
-       "e5v91s0                                           0.250000    \n",
-       "e6n6di6                                           0.250000    \n",
-       "e6iqq30                                           0.333333    \n",
-       "e5bfad7                                           0.333333    \n",
-       "e6x5he5                                           1.000000    \n",
-       "e6l9uyf                                           0.250000    \n",
-       "e57hyr1                                           0.200000    \n",
-       "e5b8sj7                                           0.166667    \n",
-       "e6nlep7                                           0.000000    \n",
-       "e6ltazd                                           0.200000    \n",
-       "e57a6qq                                           0.333333    \n",
-       "e5qc7eb                                           0.166667    \n",
-       "e6hqt5y                                           0.200000    \n",
-       "e5ua84v                                           0.250000    \n",
-       "e65m7kq                                           0.200000    \n",
-       "e5ggtru                                           0.125000    \n",
-       "e5pmmig                                           0.333333    \n",
-       "e64l6vq                                           0.400000    \n",
-       "e6fjx0d                                           0.500000    \n",
-       "e5h3xyy                                           0.200000    \n",
-       "e589ri5                                           0.333333    \n",
-       "e5beuqa                                           0.428571    \n",
-       "e5lqoj1                                           0.666667    \n",
-       "e5kvch1                                           0.200000    \n",
-       "e6srvwm                                           0.166667    \n",
-       "e5o65mk                                           0.500000    \n",
-       "e647cm8                                           0.200000    \n",
-       "e58n526                                           0.000000    \n",
-       "e69r2kg                                           0.285714    \n",
+       "         2nd-argmax[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                2.0      \n",
+       "e5ytz1d                                                4.0      \n",
+       "e6ls80j                                                1.0      \n",
+       "e5mhgl5                                                1.0      \n",
+       "e6w6fah                                                1.0      \n",
+       "...                                                    ...      \n",
+       "e65ca8k                                                0.0      \n",
+       "e6cdkpy                                                3.0      \n",
+       "e5wc4tj                                                1.0      \n",
+       "e6ua0sb                                                4.0      \n",
+       "e5ua84v                                                3.0      \n",
        "\n",
-       "         norm.max[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                 0.375000   \n",
-       "e5ywqyk                                 0.400000   \n",
-       "e5qv9rj                                 0.111111   \n",
-       "e6jhojf                                 0.500000   \n",
-       "e6989ii                                 0.500000   \n",
-       "e69lgse                                 0.250000   \n",
-       "e5kwkg2                                 0.111111   \n",
-       "e6mehe7                                 0.375000   \n",
-       "e6m0hsd                                 0.500000   \n",
-       "e64r385                                 0.222222   \n",
-       "e5surbt                                 0.111111   \n",
-       "e58gxii                                 0.375000   \n",
-       "e64vc8y                                 0.111111   \n",
-       "e57504g                                 0.222222   \n",
-       "e5borjq                                 0.222222   \n",
-       "e64n9zv                                 0.500000   \n",
-       "e582ud3                                 0.111111   \n",
-       "e64i9cf                                 0.285714   \n",
-       "e6q9204                                 0.428571   \n",
-       "e5modd7                                 0.111111   \n",
-       "e5xhbyd                                 0.333333   \n",
-       "e5oaf7h                                 0.500000   \n",
-       "e6nir3u                                 0.500000   \n",
-       "e6c3xdn                                 0.111111   \n",
-       "e5d3zaa                                 0.285714   \n",
-       "e5gnjv9                                 0.222222   \n",
-       "e69gw2t                                 0.285714   \n",
-       "e5syrih                                 0.222222   \n",
-       "e5sa2yf                                 0.500000   \n",
-       "e6ai7z5                                 0.500000   \n",
-       "...                                          ...   \n",
-       "e5smhzk                                 0.500000   \n",
-       "e5v91s0                                 0.111111   \n",
-       "e6n6di6                                 0.222222   \n",
-       "e6iqq30                                 0.111111   \n",
-       "e5bfad7                                 0.222222   \n",
-       "e6x5he5                                 0.500000   \n",
-       "e6l9uyf                                 0.222222   \n",
-       "e57hyr1                                 0.222222   \n",
-       "e5b8sj7                                 0.222222   \n",
-       "e6nlep7                                 0.111111   \n",
-       "e6ltazd                                 0.333333   \n",
-       "e57a6qq                                 0.333333   \n",
-       "e5qc7eb                                 0.285714   \n",
-       "e6hqt5y                                 0.222222   \n",
-       "e5ua84v                                 0.333333   \n",
-       "e65m7kq                                 0.222222   \n",
-       "e5ggtru                                 0.222222   \n",
-       "e5pmmig                                 0.428571   \n",
-       "e64l6vq                                 0.285714   \n",
-       "e6fjx0d                                 0.500000   \n",
-       "e5h3xyy                                 0.222222   \n",
-       "e589ri5                                 0.111111   \n",
-       "e5beuqa                                 0.444444   \n",
-       "e5lqoj1                                 0.375000   \n",
-       "e5kvch1                                 0.250000   \n",
-       "e6srvwm                                 0.222222   \n",
-       "e5o65mk                                 0.500000   \n",
-       "e647cm8                                 0.111111   \n",
-       "e58n526                                 0.111111   \n",
-       "e69r2kg                                 0.222222   \n",
+       "         2nd-argmax[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0     \n",
+       "e5ytz1d                                                0.0     \n",
+       "e6ls80j                                                4.0     \n",
+       "e5mhgl5                                                3.0     \n",
+       "e6w6fah                                                1.0     \n",
+       "...                                                    ...     \n",
+       "e65ca8k                                                0.0     \n",
+       "e6cdkpy                                                1.0     \n",
+       "e5wc4tj                                                1.0     \n",
+       "e6ua0sb                                                0.0     \n",
+       "e5ua84v                                                3.0     \n",
        "\n",
-       "         norm.max[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.500000    \n",
-       "e5ywqyk                                           0.500000    \n",
-       "e5qv9rj                                           0.166667    \n",
-       "e6jhojf                                           0.500000    \n",
-       "e6989ii                                           0.571429    \n",
-       "e69lgse                                           0.333333    \n",
-       "e5kwkg2                                           0.166667    \n",
-       "e6mehe7                                           0.500000    \n",
-       "e6m0hsd                                           0.500000    \n",
-       "e64r385                                           0.285714    \n",
-       "e5surbt                                           0.250000    \n",
-       "e58gxii                                           0.428571    \n",
-       "e64vc8y                                           0.333333    \n",
-       "e57504g                                           0.285714    \n",
-       "e5borjq                                           0.142857    \n",
-       "e64n9zv                                           0.375000    \n",
-       "e582ud3                                           0.333333    \n",
-       "e64i9cf                                           0.600000    \n",
-       "e6q9204                                           0.375000    \n",
-       "e5modd7                                           0.125000    \n",
-       "e5xhbyd                                           0.375000    \n",
-       "e5oaf7h                                           0.500000    \n",
-       "e6nir3u                                           0.571429    \n",
-       "e6c3xdn                                           0.125000    \n",
-       "e5d3zaa                                           0.285714    \n",
-       "e5gnjv9                                           1.000000    \n",
-       "e69gw2t                                           0.428571    \n",
-       "e5syrih                                           0.250000    \n",
-       "e5sa2yf                                           0.500000    \n",
-       "e6ai7z5                                           0.666667    \n",
-       "...                                                    ...    \n",
-       "e5smhzk                                           0.571429    \n",
-       "e5v91s0                                           0.250000    \n",
-       "e6n6di6                                           0.250000    \n",
-       "e6iqq30                                           0.333333    \n",
-       "e5bfad7                                           0.333333    \n",
-       "e6x5he5                                           1.000000    \n",
-       "e6l9uyf                                           0.250000    \n",
-       "e57hyr1                                           0.200000    \n",
-       "e5b8sj7                                           0.166667    \n",
-       "e6nlep7                                           0.000000    \n",
-       "e6ltazd                                           0.375000    \n",
-       "e57a6qq                                           0.375000    \n",
-       "e5qc7eb                                           0.285714    \n",
-       "e6hqt5y                                           0.200000    \n",
-       "e5ua84v                                           0.250000    \n",
-       "e65m7kq                                           0.200000    \n",
-       "e5ggtru                                           0.125000    \n",
-       "e5pmmig                                           0.375000    \n",
-       "e64l6vq                                           0.500000    \n",
-       "e6fjx0d                                           0.571429    \n",
-       "e5h3xyy                                           0.200000    \n",
-       "e589ri5                                           0.333333    \n",
-       "e5beuqa                                           0.428571    \n",
-       "e5lqoj1                                           0.500000    \n",
-       "e5kvch1                                           0.333333    \n",
-       "e6srvwm                                           0.166667    \n",
-       "e5o65mk                                           0.571429    \n",
-       "e647cm8                                           0.200000    \n",
-       "e58n526                                           0.000000    \n",
-       "e69r2kg                                           0.285714    \n",
+       "         norm.2nd-largest[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.285714            \n",
+       "e5ytz1d                                           0.166667            \n",
+       "e6ls80j                                           0.200000            \n",
+       "e5mhgl5                                           0.142857            \n",
+       "e6w6fah                                                NaN            \n",
+       "...                                                    ...            \n",
+       "e65ca8k                                           0.000000            \n",
+       "e6cdkpy                                           0.200000            \n",
+       "e5wc4tj                                           0.500000            \n",
+       "e6ua0sb                                           0.285714            \n",
+       "e5ua84v                                           0.250000            \n",
        "\n",
-       "         norm.max[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                 0.333333   \n",
-       "e5ywqyk                                 0.444444   \n",
-       "e5qv9rj                                 0.111111   \n",
-       "e6jhojf                                 0.444444   \n",
-       "e6989ii                                 0.500000   \n",
-       "e69lgse                                 0.222222   \n",
-       "e5kwkg2                                 0.111111   \n",
-       "e6mehe7                                 0.333333   \n",
-       "e6m0hsd                                 0.555556   \n",
-       "e64r385                                 0.222222   \n",
-       "e5surbt                                 0.111111   \n",
-       "e58gxii                                 0.333333   \n",
-       "e64vc8y                                 0.111111   \n",
-       "e57504g                                 0.222222   \n",
-       "e5borjq                                 0.222222   \n",
-       "e64n9zv                                 0.444444   \n",
-       "e582ud3                                 0.111111   \n",
-       "e64i9cf                                 0.333333   \n",
-       "e6q9204                                 0.444444   \n",
-       "e5modd7                                 0.111111   \n",
-       "e5xhbyd                                 0.333333   \n",
-       "e5oaf7h                                 0.555556   \n",
-       "e6nir3u                                 0.500000   \n",
-       "e6c3xdn                                 0.111111   \n",
-       "e5d3zaa                                 0.333333   \n",
-       "e5gnjv9                                 0.222222   \n",
-       "e69gw2t                                 0.333333   \n",
-       "e5syrih                                 0.222222   \n",
-       "e5sa2yf                                 0.555556   \n",
-       "e6ai7z5                                 0.555556   \n",
-       "...                                          ...   \n",
-       "e5smhzk                                 0.444444   \n",
-       "e5v91s0                                 0.111111   \n",
-       "e6n6di6                                 0.222222   \n",
-       "e6iqq30                                 0.111111   \n",
-       "e5bfad7                                 0.222222   \n",
-       "e6x5he5                                 0.500000   \n",
-       "e6l9uyf                                 0.222222   \n",
-       "e57hyr1                                 0.222222   \n",
-       "e5b8sj7                                 0.222222   \n",
-       "e6nlep7                                 0.111111   \n",
-       "e6ltazd                                 0.333333   \n",
-       "e57a6qq                                 0.333333   \n",
-       "e5qc7eb                                 0.222222   \n",
-       "e6hqt5y                                 0.222222   \n",
-       "e5ua84v                                 0.333333   \n",
-       "e65m7kq                                 0.222222   \n",
-       "e5ggtru                                 0.222222   \n",
-       "e5pmmig                                 0.333333   \n",
-       "e64l6vq                                 0.333333   \n",
-       "e6fjx0d                                 0.444444   \n",
-       "e5h3xyy                                 0.222222   \n",
-       "e589ri5                                 0.111111   \n",
-       "e5beuqa                                 0.444444   \n",
-       "e5lqoj1                                 0.333333   \n",
-       "e5kvch1                                 0.222222   \n",
-       "e6srvwm                                 0.222222   \n",
-       "e5o65mk                                 0.500000   \n",
-       "e647cm8                                 0.111111   \n",
-       "e58n526                                 0.111111   \n",
-       "e69r2kg                                 0.222222   \n",
+       "         norm.2nd-largest[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.142857           \n",
+       "e5ytz1d                                           0.333333           \n",
+       "e6ls80j                                           0.200000           \n",
+       "e5mhgl5                                           0.285714           \n",
+       "e6w6fah                                                NaN           \n",
+       "...                                                    ...           \n",
+       "e65ca8k                                           0.000000           \n",
+       "e6cdkpy                                           0.400000           \n",
+       "e5wc4tj                                           0.500000           \n",
+       "e6ua0sb                                           0.142857           \n",
+       "e5ua84v                                           0.250000           \n",
        "\n",
-       "         prop-multiple[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.250000        \n",
-       "e5ywqyk                                           0.333333        \n",
-       "e5qv9rj                                           0.250000        \n",
-       "e6jhojf                                           0.200000        \n",
-       "e6989ii                                           0.000000        \n",
-       "e69lgse                                           0.250000        \n",
-       "e5kwkg2                                           0.200000        \n",
-       "e6mehe7                                           0.250000        \n",
-       "e6m0hsd                                           0.333333        \n",
-       "e64r385                                           0.400000        \n",
-       "e5surbt                                           0.000000        \n",
-       "e58gxii                                           0.500000        \n",
-       "e64vc8y                                           0.000000        \n",
-       "e57504g                                           0.400000        \n",
-       "e5borjq                                           0.500000        \n",
-       "e64n9zv                                           0.333333        \n",
-       "e582ud3                                           0.500000        \n",
-       "e64i9cf                                           0.333333        \n",
-       "e6q9204                                           0.666667        \n",
-       "e5modd7                                           1.000000        \n",
-       "e5xhbyd                                           0.500000        \n",
-       "e5oaf7h                                           0.500000        \n",
-       "e6nir3u                                           0.000000        \n",
-       "e6c3xdn                                           0.142857        \n",
-       "e5d3zaa                                           0.666667        \n",
-       "e5gnjv9                                           0.000000        \n",
-       "e69gw2t                                           0.666667        \n",
-       "e5syrih                                           1.000000        \n",
-       "e5sa2yf                                           0.000000        \n",
-       "e6ai7z5                                           0.200000        \n",
-       "...                                                    ...        \n",
-       "e5smhzk                                           0.000000        \n",
-       "e5v91s0                                           0.333333        \n",
-       "e6n6di6                                           0.500000        \n",
-       "e6iqq30                                           0.000000        \n",
-       "e5bfad7                                           0.500000        \n",
-       "e6x5he5                                           0.000000        \n",
-       "e6l9uyf                                           0.333333        \n",
-       "e57hyr1                                           0.250000        \n",
-       "e5b8sj7                                           1.000000        \n",
-       "e6nlep7                                           0.000000        \n",
-       "e6ltazd                                           0.500000        \n",
-       "e57a6qq                                           0.666667        \n",
-       "e5qc7eb                                           0.666667        \n",
-       "e6hqt5y                                           0.500000        \n",
-       "e5ua84v                                           0.500000        \n",
-       "e65m7kq                                           0.333333        \n",
-       "e5ggtru                                           0.666667        \n",
-       "e5pmmig                                           0.500000        \n",
-       "e64l6vq                                           0.250000        \n",
-       "e6fjx0d                                           0.000000        \n",
-       "e5h3xyy                                           0.250000        \n",
-       "e589ri5                                           0.000000        \n",
-       "e5beuqa                                           0.250000        \n",
-       "e5lqoj1                                           0.000000        \n",
-       "e5kvch1                                           0.250000        \n",
-       "e6srvwm                                           0.500000        \n",
-       "e5o65mk                                           0.000000        \n",
-       "e647cm8                                           0.333333        \n",
-       "e58n526                                           0.000000        \n",
-       "e69r2kg                                           0.500000        \n",
+       "         mean[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                        1.400000   \n",
+       "e5ytz1d                                        0.666667   \n",
+       "e6ls80j                                        0.833333   \n",
+       "e5mhgl5                                        1.000000   \n",
+       "e6w6fah                                        0.000000   \n",
+       "...                                                 ...   \n",
+       "e65ca8k                                        0.500000   \n",
+       "e6cdkpy                                        0.555556   \n",
+       "e5wc4tj                                        1.000000   \n",
+       "e6ua0sb                                        1.400000   \n",
+       "e5ua84v                                        1.333333   \n",
        "\n",
-       "         prop-multiple[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                     0.250000   \n",
-       "e5ywqyk                                     0.666667   \n",
-       "e5qv9rj                                     0.400000   \n",
-       "e6jhojf                                     0.200000   \n",
-       "e6989ii                                     0.000000   \n",
-       "e69lgse                                     0.500000   \n",
-       "e5kwkg2                                     0.333333   \n",
-       "e6mehe7                                     0.500000   \n",
-       "e6m0hsd                                     0.333333   \n",
-       "e64r385                                     0.500000   \n",
-       "e5surbt                                     0.200000   \n",
-       "e58gxii                                     0.500000   \n",
-       "e64vc8y                                     0.250000   \n",
-       "e57504g                                     0.500000   \n",
-       "e5borjq                                     0.600000   \n",
-       "e64n9zv                                     0.333333   \n",
-       "e582ud3                                     0.666667   \n",
-       "e64i9cf                                     0.666667   \n",
-       "e6q9204                                     0.500000   \n",
-       "e5modd7                                     0.750000   \n",
-       "e5xhbyd                                     0.500000   \n",
-       "e5oaf7h                                     0.500000   \n",
-       "e6nir3u                                     0.000000   \n",
-       "e6c3xdn                                     0.125000   \n",
-       "e5d3zaa                                     0.750000   \n",
-       "e5gnjv9                                     0.500000   \n",
-       "e69gw2t                                     0.750000   \n",
-       "e5syrih                                     0.750000   \n",
-       "e5sa2yf                                     0.000000   \n",
-       "e6ai7z5                                     0.400000   \n",
-       "...                                              ...   \n",
-       "e5smhzk                                     0.333333   \n",
-       "e5v91s0                                     0.500000   \n",
-       "e6n6di6                                     0.400000   \n",
-       "e6iqq30                                     0.250000   \n",
-       "e5bfad7                                     0.750000   \n",
-       "e6x5he5                                     0.200000   \n",
-       "e6l9uyf                                     0.500000   \n",
-       "e57hyr1                                     0.400000   \n",
-       "e5b8sj7                                     1.000000   \n",
-       "e6nlep7                                     1.000000   \n",
-       "e6ltazd                                     0.333333   \n",
-       "e57a6qq                                     0.666667   \n",
-       "e5qc7eb                                     0.666667   \n",
-       "e6hqt5y                                     0.666667   \n",
-       "e5ua84v                                     0.400000   \n",
-       "e65m7kq                                     0.500000   \n",
-       "e5ggtru                                     0.500000   \n",
-       "e5pmmig                                     0.400000   \n",
-       "e64l6vq                                     0.500000   \n",
-       "e6fjx0d                                     0.333333   \n",
-       "e5h3xyy                                     0.400000   \n",
-       "e589ri5                                     0.250000   \n",
-       "e5beuqa                                     0.400000   \n",
-       "e5lqoj1                                     0.250000   \n",
-       "e5kvch1                                     0.400000   \n",
-       "e6srvwm                                     0.600000   \n",
-       "e5o65mk                                     0.000000   \n",
-       "e647cm8                                     0.500000   \n",
-       "e58n526                                     1.000000   \n",
-       "e69r2kg                                     0.600000   \n",
+       "         mean[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                       1.400000   \n",
+       "e5ytz1d                                       0.666667   \n",
+       "e6ls80j                                       0.833333   \n",
+       "e5mhgl5                                       1.000000   \n",
+       "e6w6fah                                       0.000000   \n",
+       "...                                                ...   \n",
+       "e65ca8k                                       0.500000   \n",
+       "e6cdkpy                                       0.555556   \n",
+       "e5wc4tj                                       1.000000   \n",
+       "e6ua0sb                                       1.400000   \n",
+       "e5ua84v                                       1.333333   \n",
        "\n",
-       "         prop-multiple[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.000000        \n",
-       "e5ywqyk                                           0.142857        \n",
-       "e5qv9rj                                           0.250000        \n",
-       "e6jhojf                                           0.142857        \n",
-       "e6989ii                                           0.000000        \n",
-       "e69lgse                                           0.250000        \n",
-       "e5kwkg2                                           0.200000        \n",
-       "e6mehe7                                           0.200000        \n",
-       "e6m0hsd                                           0.142857        \n",
-       "e64r385                                           0.400000        \n",
-       "e5surbt                                           0.000000        \n",
-       "e58gxii                                           0.400000        \n",
-       "e64vc8y                                           0.000000        \n",
-       "e57504g                                           0.400000        \n",
-       "e5borjq                                           0.500000        \n",
-       "e64n9zv                                           0.142857        \n",
-       "e582ud3                                           0.500000        \n",
-       "e64i9cf                                           0.250000        \n",
-       "e6q9204                                           0.333333        \n",
-       "e5modd7                                           1.000000        \n",
-       "e5xhbyd                                           0.333333        \n",
-       "e5oaf7h                                           0.333333        \n",
-       "e6nir3u                                           0.000000        \n",
-       "e6c3xdn                                           0.142857        \n",
-       "e5d3zaa                                           0.400000        \n",
-       "e5gnjv9                                           0.000000        \n",
-       "e69gw2t                                           0.400000        \n",
-       "e5syrih                                           0.400000        \n",
-       "e5sa2yf                                           0.000000        \n",
-       "e6ai7z5                                           0.000000        \n",
+       "         mean-nonzero[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.750000        \n",
+       "e5ytz1d                                           1.000000        \n",
+       "e6ls80j                                           1.250000        \n",
+       "e5mhgl5                                           1.166667        \n",
+       "e6w6fah                                           0.000000        \n",
        "...                                                    ...        \n",
-       "e5smhzk                                           0.000000        \n",
-       "e5v91s0                                           0.333333        \n",
-       "e6n6di6                                           0.400000        \n",
-       "e6iqq30                                           0.000000        \n",
-       "e5bfad7                                           0.500000        \n",
-       "e6x5he5                                           0.000000        \n",
-       "e6l9uyf                                           0.333333        \n",
-       "e57hyr1                                           0.250000        \n",
-       "e5b8sj7                                           0.666667        \n",
-       "e6nlep7                                           0.000000        \n",
-       "e6ltazd                                           0.200000        \n",
-       "e57a6qq                                           0.333333        \n",
-       "e5qc7eb                                           0.500000        \n",
-       "e6hqt5y                                           0.500000        \n",
-       "e5ua84v                                           0.400000        \n",
-       "e65m7kq                                           0.250000        \n",
-       "e5ggtru                                           0.500000        \n",
-       "e5pmmig                                           0.142857        \n",
-       "e64l6vq                                           0.200000        \n",
-       "e6fjx0d                                           0.000000        \n",
-       "e5h3xyy                                           0.250000        \n",
-       "e589ri5                                           0.000000        \n",
-       "e5beuqa                                           0.200000        \n",
-       "e5lqoj1                                           0.000000        \n",
-       "e5kvch1                                           0.000000        \n",
-       "e6srvwm                                           0.500000        \n",
-       "e5o65mk                                           0.000000        \n",
-       "e647cm8                                           0.333333        \n",
-       "e58n526                                           0.000000        \n",
-       "e69r2kg                                           0.400000        \n",
+       "e65ca8k                                           1.000000        \n",
+       "e6cdkpy                                           1.000000        \n",
+       "e5wc4tj                                           1.000000        \n",
+       "e6ua0sb                                           1.400000        \n",
+       "e5ua84v                                           1.333333        \n",
        "\n",
-       "         prop-multiple[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                     0.142857   \n",
-       "e5ywqyk                                     0.125000   \n",
-       "e5qv9rj                                     0.400000   \n",
-       "e6jhojf                                     0.125000   \n",
-       "e6989ii                                     0.000000   \n",
-       "e69lgse                                     0.400000   \n",
-       "e5kwkg2                                     0.333333   \n",
-       "e6mehe7                                     0.333333   \n",
-       "e6m0hsd                                     0.125000   \n",
-       "e64r385                                     0.500000   \n",
-       "e5surbt                                     0.200000   \n",
-       "e58gxii                                     0.500000   \n",
-       "e64vc8y                                     0.250000   \n",
-       "e57504g                                     0.500000   \n",
-       "e5borjq                                     0.600000   \n",
-       "e64n9zv                                     0.125000   \n",
-       "e582ud3                                     0.666667   \n",
-       "e64i9cf                                     0.400000   \n",
-       "e6q9204                                     0.285714   \n",
-       "e5modd7                                     0.750000   \n",
-       "e5xhbyd                                     0.285714   \n",
-       "e5oaf7h                                     0.285714   \n",
-       "e6nir3u                                     0.000000   \n",
-       "e6c3xdn                                     0.125000   \n",
-       "e5d3zaa                                     0.500000   \n",
-       "e5gnjv9                                     0.500000   \n",
-       "e69gw2t                                     0.500000   \n",
-       "e5syrih                                     0.333333   \n",
-       "e5sa2yf                                     0.000000   \n",
-       "e6ai7z5                                     0.142857   \n",
-       "...                                              ...   \n",
-       "e5smhzk                                     0.125000   \n",
-       "e5v91s0                                     0.500000   \n",
-       "e6n6di6                                     0.333333   \n",
-       "e6iqq30                                     0.250000   \n",
-       "e5bfad7                                     0.600000   \n",
-       "e6x5he5                                     0.200000   \n",
-       "e6l9uyf                                     0.500000   \n",
-       "e57hyr1                                     0.400000   \n",
-       "e5b8sj7                                     0.750000   \n",
-       "e6nlep7                                     1.000000   \n",
-       "e6ltazd                                     0.166667   \n",
-       "e57a6qq                                     0.285714   \n",
-       "e5qc7eb                                     0.600000   \n",
-       "e6hqt5y                                     0.666667   \n",
-       "e5ua84v                                     0.333333   \n",
-       "e65m7kq                                     0.400000   \n",
-       "e5ggtru                                     0.400000   \n",
-       "e5pmmig                                     0.125000   \n",
-       "e64l6vq                                     0.333333   \n",
-       "e6fjx0d                                     0.125000   \n",
-       "e5h3xyy                                     0.400000   \n",
-       "e589ri5                                     0.250000   \n",
-       "e5beuqa                                     0.333333   \n",
-       "e5lqoj1                                     0.200000   \n",
-       "e5kvch1                                     0.142857   \n",
-       "e6srvwm                                     0.600000   \n",
-       "e5o65mk                                     0.000000   \n",
-       "e647cm8                                     0.500000   \n",
-       "e58n526                                     1.000000   \n",
-       "e69r2kg                                     0.500000   \n",
+       "         mean-nonzero[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.400000       \n",
+       "e5ytz1d                                           2.000000       \n",
+       "e6ls80j                                           1.666667       \n",
+       "e5mhgl5                                           1.400000       \n",
+       "e6w6fah                                           0.000000       \n",
+       "...                                                    ...       \n",
+       "e65ca8k                                           1.000000       \n",
+       "e6cdkpy                                           1.666667       \n",
+       "e5wc4tj                                           1.000000       \n",
+       "e6ua0sb                                           1.750000       \n",
+       "e5ua84v                                           2.000000       \n",
        "\n",
-       "         prop-multiple[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.000000        \n",
-       "e5ywqyk                                           0.142857        \n",
-       "e5qv9rj                                           0.250000        \n",
-       "e6jhojf                                           0.142857        \n",
-       "e6989ii                                           0.142857        \n",
-       "e69lgse                                           0.250000        \n",
-       "e5kwkg2                                           0.200000        \n",
-       "e6mehe7                                           0.200000        \n",
-       "e6m0hsd                                           0.142857        \n",
-       "e64r385                                           0.400000        \n",
-       "e5surbt                                           0.000000        \n",
-       "e58gxii                                           0.400000        \n",
-       "e64vc8y                                           0.000000        \n",
-       "e57504g                                           0.400000        \n",
-       "e5borjq                                           0.500000        \n",
-       "e64n9zv                                           0.142857        \n",
-       "e582ud3                                           0.500000        \n",
-       "e64i9cf                                           0.250000        \n",
-       "e6q9204                                           0.333333        \n",
-       "e5modd7                                           1.000000        \n",
-       "e5xhbyd                                           0.333333        \n",
-       "e5oaf7h                                           0.333333        \n",
-       "e6nir3u                                           0.142857        \n",
-       "e6c3xdn                                           0.142857        \n",
-       "e5d3zaa                                           0.400000        \n",
-       "e5gnjv9                                           0.000000        \n",
-       "e69gw2t                                           0.400000        \n",
-       "e5syrih                                           0.400000        \n",
-       "e5sa2yf                                           0.000000        \n",
-       "e6ai7z5                                           0.000000        \n",
+       "         prop-nonzero[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.800000        \n",
+       "e5ytz1d                                           0.666667        \n",
+       "e6ls80j                                           0.666667        \n",
+       "e5mhgl5                                           0.857143        \n",
+       "e6w6fah                                           0.000000        \n",
        "...                                                    ...        \n",
-       "e5smhzk                                           0.000000        \n",
-       "e5v91s0                                           0.333333        \n",
-       "e6n6di6                                           0.400000        \n",
-       "e6iqq30                                           0.000000        \n",
-       "e5bfad7                                           0.500000        \n",
-       "e6x5he5                                           0.250000        \n",
-       "e6l9uyf                                           0.333333        \n",
-       "e57hyr1                                           0.250000        \n",
-       "e5b8sj7                                           0.666667        \n",
-       "e6nlep7                                           0.000000        \n",
-       "e6ltazd                                           0.200000        \n",
-       "e57a6qq                                           0.333333        \n",
-       "e5qc7eb                                           0.500000        \n",
-       "e6hqt5y                                           0.500000        \n",
-       "e5ua84v                                           0.400000        \n",
-       "e65m7kq                                           0.250000        \n",
-       "e5ggtru                                           0.500000        \n",
-       "e5pmmig                                           0.142857        \n",
-       "e64l6vq                                           0.200000        \n",
-       "e6fjx0d                                           0.000000        \n",
-       "e5h3xyy                                           0.250000        \n",
-       "e589ri5                                           0.000000        \n",
-       "e5beuqa                                           0.200000        \n",
-       "e5lqoj1                                           0.000000        \n",
-       "e5kvch1                                           0.000000        \n",
-       "e6srvwm                                           0.500000        \n",
-       "e5o65mk                                           0.000000        \n",
-       "e647cm8                                           0.333333        \n",
-       "e58n526                                           0.000000        \n",
-       "e69r2kg                                           0.400000        \n",
+       "e65ca8k                                           0.500000        \n",
+       "e6cdkpy                                           0.555556        \n",
+       "e5wc4tj                                           1.000000        \n",
+       "e6ua0sb                                           1.000000        \n",
+       "e5ua84v                                           1.000000        \n",
        "\n",
-       "         prop-multiple[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                     0.142857   \n",
-       "e5ywqyk                                     0.125000   \n",
-       "e5qv9rj                                     0.400000   \n",
-       "e6jhojf                                     0.125000   \n",
-       "e6989ii                                     0.125000   \n",
-       "e69lgse                                     0.400000   \n",
-       "e5kwkg2                                     0.333333   \n",
-       "e6mehe7                                     0.333333   \n",
-       "e6m0hsd                                     0.125000   \n",
-       "e64r385                                     0.500000   \n",
-       "e5surbt                                     0.200000   \n",
-       "e58gxii                                     0.500000   \n",
-       "e64vc8y                                     0.250000   \n",
-       "e57504g                                     0.500000   \n",
-       "e5borjq                                     0.600000   \n",
-       "e64n9zv                                     0.125000   \n",
-       "e582ud3                                     0.666667   \n",
-       "e64i9cf                                     0.400000   \n",
-       "e6q9204                                     0.285714   \n",
-       "e5modd7                                     0.750000   \n",
-       "e5xhbyd                                     0.285714   \n",
-       "e5oaf7h                                     0.285714   \n",
-       "e6nir3u                                     0.125000   \n",
-       "e6c3xdn                                     0.125000   \n",
-       "e5d3zaa                                     0.500000   \n",
-       "e5gnjv9                                     0.500000   \n",
-       "e69gw2t                                     0.500000   \n",
-       "e5syrih                                     0.333333   \n",
-       "e5sa2yf                                     0.000000   \n",
-       "e6ai7z5                                     0.142857   \n",
-       "...                                              ...   \n",
-       "e5smhzk                                     0.125000   \n",
-       "e5v91s0                                     0.500000   \n",
-       "e6n6di6                                     0.333333   \n",
-       "e6iqq30                                     0.250000   \n",
-       "e5bfad7                                     0.600000   \n",
-       "e6x5he5                                     0.400000   \n",
-       "e6l9uyf                                     0.500000   \n",
-       "e57hyr1                                     0.400000   \n",
-       "e5b8sj7                                     0.750000   \n",
-       "e6nlep7                                     1.000000   \n",
-       "e6ltazd                                     0.166667   \n",
-       "e57a6qq                                     0.285714   \n",
-       "e5qc7eb                                     0.600000   \n",
-       "e6hqt5y                                     0.666667   \n",
-       "e5ua84v                                     0.333333   \n",
-       "e65m7kq                                     0.400000   \n",
-       "e5ggtru                                     0.400000   \n",
-       "e5pmmig                                     0.125000   \n",
-       "e64l6vq                                     0.333333   \n",
-       "e6fjx0d                                     0.125000   \n",
-       "e5h3xyy                                     0.400000   \n",
-       "e589ri5                                     0.250000   \n",
-       "e5beuqa                                     0.333333   \n",
-       "e5lqoj1                                     0.200000   \n",
-       "e5kvch1                                     0.142857   \n",
-       "e6srvwm                                     0.600000   \n",
-       "e5o65mk                                     0.125000   \n",
-       "e647cm8                                     0.500000   \n",
-       "e58n526                                     1.000000   \n",
-       "e69r2kg                                     0.500000   \n",
+       "         prop-nonzero[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.000000       \n",
+       "e5ytz1d                                           0.333333       \n",
+       "e6ls80j                                           0.500000       \n",
+       "e5mhgl5                                           0.714286       \n",
+       "e6w6fah                                           0.000000       \n",
+       "...                                                    ...       \n",
+       "e65ca8k                                           0.500000       \n",
+       "e6cdkpy                                           0.333333       \n",
+       "e5wc4tj                                           1.000000       \n",
+       "e6ua0sb                                           0.800000       \n",
+       "e5ua84v                                           0.666667       \n",
        "\n",
        "         prop-multiple[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.250000         \n",
-       "e5ywqyk                                           0.333333         \n",
-       "e5qv9rj                                           0.000000         \n",
-       "e6jhojf                                           0.250000         \n",
-       "e6989ii                                           0.000000         \n",
-       "e69lgse                                           0.200000         \n",
-       "e5kwkg2                                           0.000000         \n",
-       "e6mehe7                                           0.333333         \n",
-       "e6m0hsd                                           0.333333         \n",
-       "e64r385                                           0.166667         \n",
-       "e5surbt                                           0.000000         \n",
-       "e58gxii                                           0.200000         \n",
-       "e64vc8y                                           0.000000         \n",
-       "e57504g                                           0.166667         \n",
-       "e5borjq                                           0.000000         \n",
-       "e64n9zv                                           0.333333         \n",
-       "e582ud3                                           0.000000         \n",
-       "e64i9cf                                           0.333333         \n",
-       "e6q9204                                           0.200000         \n",
-       "e5modd7                                           0.000000         \n",
-       "e5xhbyd                                           0.500000         \n",
-       "e5oaf7h                                           0.333333         \n",
-       "e6nir3u                                           0.000000         \n",
-       "e6c3xdn                                           0.000000         \n",
-       "e5d3zaa                                           0.000000         \n",
-       "e5gnjv9                                           0.000000         \n",
-       "e69gw2t                                           0.250000         \n",
-       "e5syrih                                           0.142857         \n",
-       "e5sa2yf                                           0.000000         \n",
-       "e6ai7z5                                           0.333333         \n",
+       "e5hm9mp                                           0.750000         \n",
+       "e5ytz1d                                           0.000000         \n",
+       "e6ls80j                                           0.250000         \n",
+       "e5mhgl5                                           0.166667         \n",
+       "e6w6fah                                           0.000000         \n",
        "...                                                    ...         \n",
-       "e5smhzk                                           0.500000         \n",
-       "e5v91s0                                           0.000000         \n",
-       "e6n6di6                                           0.142857         \n",
-       "e6iqq30                                           0.000000         \n",
-       "e5bfad7                                           0.200000         \n",
-       "e6x5he5                                           1.000000         \n",
-       "e6l9uyf                                           0.000000         \n",
-       "e57hyr1                                           0.000000         \n",
-       "e5b8sj7                                           0.000000         \n",
-       "e6nlep7                                           0.000000         \n",
-       "e6ltazd                                           0.000000         \n",
-       "e57a6qq                                           0.200000         \n",
-       "e5qc7eb                                           0.000000         \n",
-       "e6hqt5y                                           0.000000         \n",
+       "e65ca8k                                           0.000000         \n",
+       "e6cdkpy                                           0.000000         \n",
+       "e5wc4tj                                           0.000000         \n",
+       "e6ua0sb                                           0.400000         \n",
        "e5ua84v                                           0.333333         \n",
-       "e65m7kq                                           0.000000         \n",
-       "e5ggtru                                           0.000000         \n",
-       "e5pmmig                                           0.500000         \n",
-       "e64l6vq                                           0.250000         \n",
-       "e6fjx0d                                           0.000000         \n",
-       "e5h3xyy                                           0.000000         \n",
-       "e589ri5                                           0.000000         \n",
-       "e5beuqa                                           0.200000         \n",
-       "e5lqoj1                                           0.500000         \n",
-       "e5kvch1                                           0.000000         \n",
-       "e6srvwm                                           0.000000         \n",
-       "e5o65mk                                           0.000000         \n",
-       "e647cm8                                           0.000000         \n",
-       "e58n526                                           0.000000         \n",
-       "e69r2kg                                           0.166667         \n",
        "\n",
-       "         prop-multiple[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                      0.166667   \n",
-       "e5ywqyk                                      0.250000   \n",
-       "e5qv9rj                                      0.000000   \n",
-       "e6jhojf                                      0.200000   \n",
-       "e6989ii                                      0.000000   \n",
-       "e69lgse                                      0.142857   \n",
-       "e5kwkg2                                      0.000000   \n",
-       "e6mehe7                                      0.166667   \n",
-       "e6m0hsd                                      0.333333   \n",
-       "e64r385                                      0.285714   \n",
-       "e5surbt                                      0.000000   \n",
-       "e58gxii                                      0.166667   \n",
-       "e64vc8y                                      0.000000   \n",
-       "e57504g                                      0.285714   \n",
-       "e5borjq                                      0.125000   \n",
-       "e64n9zv                                      0.333333   \n",
-       "e582ud3                                      0.000000   \n",
-       "e64i9cf                                      0.166667   \n",
-       "e6q9204                                      0.200000   \n",
-       "e5modd7                                      0.000000   \n",
-       "e5xhbyd                                      0.500000   \n",
-       "e5oaf7h                                      0.333333   \n",
-       "e6nir3u                                      0.000000   \n",
-       "e6c3xdn                                      0.000000   \n",
-       "e5d3zaa                                      0.166667   \n",
-       "e5gnjv9                                      0.125000   \n",
-       "e69gw2t                                      0.400000   \n",
-       "e5syrih                                      0.285714   \n",
-       "e5sa2yf                                      0.000000   \n",
-       "e6ai7z5                                      0.200000   \n",
-       "...                                               ...   \n",
-       "e5smhzk                                      0.333333   \n",
-       "e5v91s0                                      0.000000   \n",
-       "e6n6di6                                      0.125000   \n",
-       "e6iqq30                                      0.000000   \n",
-       "e5bfad7                                      0.125000   \n",
-       "e6x5he5                                      0.200000   \n",
-       "e6l9uyf                                      0.125000   \n",
-       "e57hyr1                                      0.500000   \n",
-       "e5b8sj7                                      0.125000   \n",
-       "e6nlep7                                      0.000000   \n",
-       "e6ltazd                                      0.200000   \n",
-       "e57a6qq                                      0.200000   \n",
-       "e5qc7eb                                      0.166667   \n",
-       "e6hqt5y                                      0.125000   \n",
-       "e5ua84v                                      0.333333   \n",
-       "e65m7kq                                      0.125000   \n",
-       "e5ggtru                                      0.125000   \n",
-       "e5pmmig                                      0.500000   \n",
-       "e64l6vq                                      0.166667   \n",
-       "e6fjx0d                                      0.333333   \n",
-       "e5h3xyy                                      0.125000   \n",
-       "e589ri5                                      0.000000   \n",
-       "e5beuqa                                      0.400000   \n",
-       "e5lqoj1                                      0.166667   \n",
-       "e5kvch1                                      0.333333   \n",
-       "e6srvwm                                      0.125000   \n",
-       "e5o65mk                                      0.000000   \n",
-       "e647cm8                                      0.000000   \n",
-       "e58n526                                      0.000000   \n",
-       "e69r2kg                                      0.125000   \n",
+       "         prop-multiple[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.200000        \n",
+       "e5ytz1d                                           0.666667        \n",
+       "e6ls80j                                           0.333333        \n",
+       "e5mhgl5                                           0.400000        \n",
+       "e6w6fah                                           0.000000        \n",
+       "...                                                    ...        \n",
+       "e65ca8k                                           0.000000        \n",
+       "e6cdkpy                                           0.666667        \n",
+       "e5wc4tj                                           0.000000        \n",
+       "e6ua0sb                                           0.250000        \n",
+       "e5ua84v                                           0.500000        \n",
        "\n",
-       "         prop-multiple[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.250000         \n",
-       "e5ywqyk                                           0.666667         \n",
-       "e5qv9rj                                           0.000000         \n",
-       "e6jhojf                                           0.500000         \n",
-       "e6989ii                                           1.000000         \n",
-       "e69lgse                                           0.200000         \n",
-       "e5kwkg2                                           0.000000         \n",
-       "e6mehe7                                           0.666667         \n",
-       "e6m0hsd                                           0.666667         \n",
-       "e64r385                                           0.166667         \n",
-       "e5surbt                                           0.000000         \n",
-       "e58gxii                                           0.200000         \n",
-       "e64vc8y                                           0.000000         \n",
-       "e57504g                                           0.166667         \n",
-       "e5borjq                                           0.000000         \n",
-       "e64n9zv                                           1.000000         \n",
-       "e582ud3                                           0.000000         \n",
-       "e64i9cf                                           0.333333         \n",
-       "e6q9204                                           0.400000         \n",
-       "e5modd7                                           0.000000         \n",
-       "e5xhbyd                                           0.750000         \n",
-       "e5oaf7h                                           0.666667         \n",
-       "e6nir3u                                           1.000000         \n",
-       "e6c3xdn                                           0.000000         \n",
-       "e5d3zaa                                           0.400000         \n",
-       "e5gnjv9                                           0.000000         \n",
-       "e69gw2t                                           0.500000         \n",
-       "e5syrih                                           0.142857         \n",
-       "e5sa2yf                                           1.000000         \n",
-       "e6ai7z5                                           0.333333         \n",
-       "...                                                    ...         \n",
-       "e5smhzk                                           1.000000         \n",
-       "e5v91s0                                           0.000000         \n",
-       "e6n6di6                                           0.142857         \n",
-       "e6iqq30                                           0.000000         \n",
-       "e5bfad7                                           0.200000         \n",
-       "e6x5he5                                           1.000000         \n",
-       "e6l9uyf                                           0.000000         \n",
-       "e57hyr1                                           0.000000         \n",
-       "e5b8sj7                                           0.000000         \n",
-       "e6nlep7                                           0.000000         \n",
-       "e6ltazd                                           0.400000         \n",
-       "e57a6qq                                           0.400000         \n",
-       "e5qc7eb                                           0.166667         \n",
-       "e6hqt5y                                           0.000000         \n",
-       "e5ua84v                                           0.333333         \n",
-       "e65m7kq                                           0.000000         \n",
-       "e5ggtru                                           0.000000         \n",
-       "e5pmmig                                           0.750000         \n",
-       "e64l6vq                                           0.250000         \n",
-       "e6fjx0d                                           1.000000         \n",
-       "e5h3xyy                                           0.000000         \n",
-       "e589ri5                                           0.000000         \n",
-       "e5beuqa                                           0.200000         \n",
-       "e5lqoj1                                           1.000000         \n",
-       "e5kvch1                                           0.200000         \n",
-       "e6srvwm                                           0.000000         \n",
-       "e5o65mk                                           1.000000         \n",
-       "e647cm8                                           0.000000         \n",
-       "e58n526                                           0.000000         \n",
-       "e69r2kg                                           0.166667         \n",
+       "         entropy[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           1.351784   \n",
+       "e5ytz1d                                           1.791759   \n",
+       "e6ls80j                                           1.332179   \n",
+       "e5mhgl5                                           1.747868   \n",
+       "e6w6fah                                                NaN   \n",
+       "...                                                    ...   \n",
+       "e65ca8k                                           0.000000   \n",
+       "e6cdkpy                                           1.609438   \n",
+       "e5wc4tj                                           0.693147   \n",
+       "e6ua0sb                                           1.549826   \n",
+       "e5ua84v                                           1.732868   \n",
        "\n",
-       "         prop-multiple[outdegree over C->c responses]  \\\n",
-       "e6p7yrp                                      0.333333   \n",
-       "e5ywqyk                                      0.500000   \n",
-       "e5qv9rj                                      0.000000   \n",
-       "e6jhojf                                      0.400000   \n",
-       "e6989ii                                      1.000000   \n",
-       "e69lgse                                      0.285714   \n",
-       "e5kwkg2                                      0.000000   \n",
-       "e6mehe7                                      0.333333   \n",
-       "e6m0hsd                                      0.666667   \n",
-       "e64r385                                      0.285714   \n",
-       "e5surbt                                      0.000000   \n",
-       "e58gxii                                      0.333333   \n",
-       "e64vc8y                                      0.000000   \n",
-       "e57504g                                      0.285714   \n",
-       "e5borjq                                      0.125000   \n",
-       "e64n9zv                                      1.000000   \n",
-       "e582ud3                                      0.000000   \n",
-       "e64i9cf                                      0.333333   \n",
-       "e6q9204                                      0.400000   \n",
-       "e5modd7                                      0.000000   \n",
-       "e5xhbyd                                      0.750000   \n",
-       "e5oaf7h                                      0.666667   \n",
-       "e6nir3u                                      1.000000   \n",
-       "e6c3xdn                                      0.000000   \n",
-       "e5d3zaa                                      0.333333   \n",
-       "e5gnjv9                                      0.125000   \n",
-       "e69gw2t                                      0.400000   \n",
-       "e5syrih                                      0.285714   \n",
-       "e5sa2yf                                      1.000000   \n",
-       "e6ai7z5                                      0.200000   \n",
-       "...                                               ...   \n",
-       "e5smhzk                                      0.666667   \n",
-       "e5v91s0                                      0.000000   \n",
-       "e6n6di6                                      0.125000   \n",
-       "e6iqq30                                      0.000000   \n",
-       "e5bfad7                                      0.125000   \n",
-       "e6x5he5                                      0.200000   \n",
-       "e6l9uyf                                      0.125000   \n",
-       "e57hyr1                                      0.500000   \n",
-       "e5b8sj7                                      0.125000   \n",
-       "e6nlep7                                      0.000000   \n",
-       "e6ltazd                                      0.400000   \n",
-       "e57a6qq                                      0.400000   \n",
-       "e5qc7eb                                      0.500000   \n",
-       "e6hqt5y                                      0.125000   \n",
-       "e5ua84v                                      0.333333   \n",
-       "e65m7kq                                      0.125000   \n",
-       "e5ggtru                                      0.125000   \n",
-       "e5pmmig                                      0.750000   \n",
-       "e64l6vq                                      0.333333   \n",
-       "e6fjx0d                                      0.666667   \n",
-       "e5h3xyy                                      0.125000   \n",
-       "e589ri5                                      0.000000   \n",
-       "e5beuqa                                      0.400000   \n",
-       "e5lqoj1                                      0.333333   \n",
-       "e5kvch1                                      0.500000   \n",
-       "e6srvwm                                      0.125000   \n",
-       "e5o65mk                                      1.000000   \n",
-       "e647cm8                                      0.000000   \n",
-       "e58n526                                      0.000000   \n",
-       "e69r2kg                                      0.125000   \n",
+       "         entropy[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                          1.475076   \n",
+       "e5ytz1d                                          1.011404   \n",
+       "e6ls80j                                          0.950271   \n",
+       "e5mhgl5                                          1.549826   \n",
+       "e6w6fah                                               NaN   \n",
+       "...                                                   ...   \n",
+       "e65ca8k                                          0.000000   \n",
+       "e6cdkpy                                          1.054920   \n",
+       "e5wc4tj                                          0.693147   \n",
+       "e6ua0sb                                          1.153742   \n",
+       "e5ua84v                                          1.213008   \n",
        "\n",
-       "         prop-nonzero[indegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.666667       \n",
-       "e5ywqyk                                           0.750000       \n",
-       "e5qv9rj                                           0.444444       \n",
-       "e6jhojf                                           1.000000       \n",
-       "e6989ii                                           1.000000       \n",
-       "e69lgse                                           0.571429       \n",
-       "e5kwkg2                                           0.555556       \n",
-       "e6mehe7                                           0.666667       \n",
-       "e6m0hsd                                           1.000000       \n",
-       "e64r385                                           0.714286       \n",
-       "e5surbt                                           0.444444       \n",
-       "e58gxii                                           0.666667       \n",
-       "e64vc8y                                           0.333333       \n",
-       "e57504g                                           0.714286       \n",
-       "e5borjq                                           0.500000       \n",
-       "e64n9zv                                           1.000000       \n",
-       "e582ud3                                           0.222222       \n",
-       "e64i9cf                                           0.500000       \n",
-       "e6q9204                                           0.600000       \n",
-       "e5modd7                                           0.333333       \n",
-       "e5xhbyd                                           1.000000       \n",
-       "e5oaf7h                                           0.666667       \n",
-       "e6nir3u                                           1.000000       \n",
-       "e6c3xdn                                           0.777778       \n",
-       "e5d3zaa                                           0.500000       \n",
-       "e5gnjv9                                           0.125000       \n",
-       "e69gw2t                                           0.600000       \n",
-       "e5syrih                                           0.428571       \n",
-       "e5sa2yf                                           1.000000       \n",
-       "e6ai7z5                                           1.000000       \n",
-       "...                                                    ...       \n",
-       "e5smhzk                                           1.000000       \n",
-       "e5v91s0                                           0.333333       \n",
-       "e6n6di6                                           0.500000       \n",
-       "e6iqq30                                           0.333333       \n",
-       "e5bfad7                                           0.500000       \n",
-       "e6x5he5                                           0.800000       \n",
-       "e6l9uyf                                           0.375000       \n",
-       "e57hyr1                                           0.666667       \n",
-       "e5b8sj7                                           0.250000       \n",
-       "e6nlep7                                           0.000000       \n",
-       "e6ltazd                                           0.400000       \n",
-       "e57a6qq                                           0.600000       \n",
-       "e5qc7eb                                           0.500000       \n",
-       "e6hqt5y                                           0.250000       \n",
-       "e5ua84v                                           0.666667       \n",
-       "e65m7kq                                           0.375000       \n",
-       "e5ggtru                                           0.375000       \n",
-       "e5pmmig                                           1.000000       \n",
-       "e64l6vq                                           0.666667       \n",
-       "e6fjx0d                                           0.666667       \n",
-       "e5h3xyy                                           0.500000       \n",
-       "e589ri5                                           0.333333       \n",
-       "e5beuqa                                           0.800000       \n",
-       "e5lqoj1                                           0.500000       \n",
-       "e5kvch1                                           0.666667       \n",
-       "e6srvwm                                           0.500000       \n",
-       "e5o65mk                                           1.000000       \n",
-       "e647cm8                                           0.333333       \n",
-       "e58n526                                           0.000000       \n",
-       "e69r2kg                                           0.500000       \n",
+       "         2nd-largest / max[outdegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                                1.0             \n",
+       "e5ytz1d                                                1.0             \n",
+       "e6ls80j                                                0.5             \n",
+       "e5mhgl5                                                0.5             \n",
+       "e6w6fah                                                NaN             \n",
+       "...                                                    ...             \n",
+       "e65ca8k                                                0.0             \n",
+       "e6cdkpy                                                1.0             \n",
+       "e5wc4tj                                                1.0             \n",
+       "e6ua0sb                                                1.0             \n",
+       "e5ua84v                                                1.0             \n",
        "\n",
-       "         prop-nonzero[indegree over C->C responses]  \\\n",
-       "e6p7yrp                                    0.666667   \n",
-       "e5ywqyk                                    0.750000   \n",
-       "e5qv9rj                                    0.500000   \n",
-       "e6jhojf                                    1.000000   \n",
-       "e6989ii                                    1.000000   \n",
-       "e69lgse                                    0.571429   \n",
-       "e5kwkg2                                    0.600000   \n",
-       "e6mehe7                                    0.666667   \n",
-       "e6m0hsd                                    1.000000   \n",
-       "e64r385                                    0.750000   \n",
-       "e5surbt                                    0.500000   \n",
-       "e58gxii                                    0.666667   \n",
-       "e64vc8y                                    0.400000   \n",
-       "e57504g                                    0.750000   \n",
-       "e5borjq                                    0.625000   \n",
-       "e64n9zv                                    1.000000   \n",
-       "e582ud3                                    0.300000   \n",
-       "e64i9cf                                    0.500000   \n",
-       "e6q9204                                    0.666667   \n",
-       "e5modd7                                    0.400000   \n",
-       "e5xhbyd                                    1.000000   \n",
-       "e5oaf7h                                    0.666667   \n",
-       "e6nir3u                                    1.000000   \n",
-       "e6c3xdn                                    0.800000   \n",
-       "e5d3zaa                                    0.571429   \n",
-       "e5gnjv9                                    0.222222   \n",
-       "e69gw2t                                    0.800000   \n",
-       "e5syrih                                    0.571429   \n",
-       "e5sa2yf                                    1.000000   \n",
-       "e6ai7z5                                    1.000000   \n",
-       "...                                             ...   \n",
-       "e5smhzk                                    1.000000   \n",
-       "e5v91s0                                    0.400000   \n",
-       "e6n6di6                                    0.555556   \n",
-       "e6iqq30                                    0.444444   \n",
-       "e5bfad7                                    0.500000   \n",
-       "e6x5he5                                    1.000000   \n",
-       "e6l9uyf                                    0.444444   \n",
-       "e57hyr1                                    0.714286   \n",
-       "e5b8sj7                                    0.375000   \n",
-       "e6nlep7                                    0.100000   \n",
-       "e6ltazd                                    0.500000   \n",
-       "e57a6qq                                    0.600000   \n",
-       "e5qc7eb                                    0.500000   \n",
-       "e6hqt5y                                    0.333333   \n",
-       "e5ua84v                                    0.714286   \n",
-       "e65m7kq                                    0.444444   \n",
-       "e5ggtru                                    0.444444   \n",
-       "e5pmmig                                    1.000000   \n",
-       "e64l6vq                                    0.666667   \n",
-       "e6fjx0d                                    0.750000   \n",
-       "e5h3xyy                                    0.555556   \n",
-       "e589ri5                                    0.400000   \n",
-       "e5beuqa                                    0.833333   \n",
-       "e5lqoj1                                    0.571429   \n",
-       "e5kvch1                                    0.714286   \n",
-       "e6srvwm                                    0.555556   \n",
-       "e5o65mk                                    1.000000   \n",
-       "e647cm8                                    0.444444   \n",
-       "e58n526                                    0.100000   \n",
-       "e69r2kg                                    0.625000   \n",
+       "         2nd-largest / max[indegree over C->C mid-thread responses]  \\\n",
+       "e5hm9mp                                           0.333333            \n",
+       "e5ytz1d                                           0.666667            \n",
+       "e6ls80j                                           0.333333            \n",
+       "e5mhgl5                                           1.000000            \n",
+       "e6w6fah                                                NaN            \n",
+       "...                                                    ...            \n",
+       "e65ca8k                                           0.000000            \n",
+       "e6cdkpy                                           1.000000            \n",
+       "e5wc4tj                                           1.000000            \n",
+       "e6ua0sb                                           0.250000            \n",
+       "e5ua84v                                           0.500000            \n",
        "\n",
-       "         prop-nonzero[indegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.666667       \n",
-       "e5ywqyk                                           0.777778       \n",
-       "e5qv9rj                                           0.444444       \n",
-       "e6jhojf                                           0.777778       \n",
-       "e6989ii                                           0.777778       \n",
-       "e69lgse                                           0.444444       \n",
-       "e5kwkg2                                           0.555556       \n",
-       "e6mehe7                                           0.555556       \n",
-       "e6m0hsd                                           0.777778       \n",
-       "e64r385                                           0.555556       \n",
-       "e5surbt                                           0.444444       \n",
-       "e58gxii                                           0.555556       \n",
-       "e64vc8y                                           0.333333       \n",
-       "e57504g                                           0.555556       \n",
-       "e5borjq                                           0.444444       \n",
-       "e64n9zv                                           0.777778       \n",
-       "e582ud3                                           0.222222       \n",
-       "e64i9cf                                           0.444444       \n",
-       "e6q9204                                           0.666667       \n",
-       "e5modd7                                           0.333333       \n",
-       "e5xhbyd                                           0.666667       \n",
-       "e5oaf7h                                           0.666667       \n",
-       "e6nir3u                                           0.777778       \n",
-       "e6c3xdn                                           0.777778       \n",
-       "e5d3zaa                                           0.555556       \n",
-       "e5gnjv9                                           0.111111       \n",
-       "e69gw2t                                           0.555556       \n",
-       "e5syrih                                           0.555556       \n",
-       "e5sa2yf                                           0.888889       \n",
-       "e6ai7z5                                           0.666667       \n",
-       "...                                                    ...       \n",
-       "e5smhzk                                           0.777778       \n",
-       "e5v91s0                                           0.333333       \n",
-       "e6n6di6                                           0.555556       \n",
-       "e6iqq30                                           0.333333       \n",
-       "e5bfad7                                           0.444444       \n",
-       "e6x5he5                                           0.444444       \n",
-       "e6l9uyf                                           0.333333       \n",
-       "e57hyr1                                           0.444444       \n",
-       "e5b8sj7                                           0.333333       \n",
-       "e6nlep7                                           0.000000       \n",
-       "e6ltazd                                           0.555556       \n",
-       "e57a6qq                                           0.666667       \n",
-       "e5qc7eb                                           0.444444       \n",
-       "e6hqt5y                                           0.222222       \n",
-       "e5ua84v                                           0.555556       \n",
-       "e65m7kq                                           0.444444       \n",
-       "e5ggtru                                           0.444444       \n",
-       "e5pmmig                                           0.777778       \n",
-       "e64l6vq                                           0.555556       \n",
-       "e6fjx0d                                           0.777778       \n",
-       "e5h3xyy                                           0.444444       \n",
-       "e589ri5                                           0.333333       \n",
-       "e5beuqa                                           0.555556       \n",
-       "e5lqoj1                                           0.444444       \n",
-       "e5kvch1                                           0.666667       \n",
-       "e6srvwm                                           0.444444       \n",
-       "e5o65mk                                           0.777778       \n",
-       "e647cm8                                           0.333333       \n",
-       "e58n526                                           0.000000       \n",
-       "e69r2kg                                           0.555556       \n",
+       "         is-present[reciprocity motif over mid-thread]  \\\n",
+       "e5hm9mp                                            1.0   \n",
+       "e5ytz1d                                            0.0   \n",
+       "e6ls80j                                            1.0   \n",
+       "e5mhgl5                                            1.0   \n",
+       "e6w6fah                                            0.0   \n",
+       "...                                                ...   \n",
+       "e65ca8k                                            1.0   \n",
+       "e6cdkpy                                            0.0   \n",
+       "e5wc4tj                                            1.0   \n",
+       "e6ua0sb                                            1.0   \n",
+       "e5ua84v                                            1.0   \n",
        "\n",
-       "         prop-nonzero[indegree over C->c responses]  \\\n",
-       "e6p7yrp                                         0.7   \n",
-       "e5ywqyk                                         0.8   \n",
-       "e5qv9rj                                         0.5   \n",
-       "e6jhojf                                         0.8   \n",
-       "e6989ii                                         0.8   \n",
-       "e69lgse                                         0.5   \n",
-       "e5kwkg2                                         0.6   \n",
-       "e6mehe7                                         0.6   \n",
-       "e6m0hsd                                         0.8   \n",
-       "e64r385                                         0.6   \n",
-       "e5surbt                                         0.5   \n",
-       "e58gxii                                         0.6   \n",
-       "e64vc8y                                         0.4   \n",
-       "e57504g                                         0.6   \n",
-       "e5borjq                                         0.5   \n",
-       "e64n9zv                                         0.8   \n",
-       "e582ud3                                         0.3   \n",
-       "e64i9cf                                         0.5   \n",
-       "e6q9204                                         0.7   \n",
-       "e5modd7                                         0.4   \n",
-       "e5xhbyd                                         0.7   \n",
-       "e5oaf7h                                         0.7   \n",
-       "e6nir3u                                         0.8   \n",
-       "e6c3xdn                                         0.8   \n",
-       "e5d3zaa                                         0.6   \n",
-       "e5gnjv9                                         0.2   \n",
-       "e69gw2t                                         0.6   \n",
-       "e5syrih                                         0.6   \n",
-       "e5sa2yf                                         0.9   \n",
-       "e6ai7z5                                         0.7   \n",
-       "...                                             ...   \n",
-       "e5smhzk                                         0.8   \n",
-       "e5v91s0                                         0.4   \n",
-       "e6n6di6                                         0.6   \n",
-       "e6iqq30                                         0.4   \n",
-       "e5bfad7                                         0.5   \n",
-       "e6x5he5                                         0.5   \n",
-       "e6l9uyf                                         0.4   \n",
-       "e57hyr1                                         0.5   \n",
-       "e5b8sj7                                         0.4   \n",
-       "e6nlep7                                         0.1   \n",
-       "e6ltazd                                         0.6   \n",
-       "e57a6qq                                         0.7   \n",
-       "e5qc7eb                                         0.5   \n",
-       "e6hqt5y                                         0.3   \n",
-       "e5ua84v                                         0.6   \n",
-       "e65m7kq                                         0.5   \n",
-       "e5ggtru                                         0.5   \n",
-       "e5pmmig                                         0.8   \n",
-       "e64l6vq                                         0.6   \n",
-       "e6fjx0d                                         0.8   \n",
-       "e5h3xyy                                         0.5   \n",
-       "e589ri5                                         0.4   \n",
-       "e5beuqa                                         0.6   \n",
-       "e5lqoj1                                         0.5   \n",
-       "e5kvch1                                         0.7   \n",
-       "e6srvwm                                         0.5   \n",
-       "e5o65mk                                         0.8   \n",
-       "e647cm8                                         0.4   \n",
-       "e58n526                                         0.1   \n",
-       "e69r2kg                                         0.6   \n",
+       "         count[reciprocity motif over mid-thread]  \\\n",
+       "e5hm9mp                                       3.0   \n",
+       "e5ytz1d                                       0.0   \n",
+       "e6ls80j                                       1.0   \n",
+       "e5mhgl5                                       2.0   \n",
+       "e6w6fah                                       0.0   \n",
+       "...                                           ...   \n",
+       "e65ca8k                                       6.0   \n",
+       "e6cdkpy                                       0.0   \n",
+       "e5wc4tj                                       7.0   \n",
+       "e6ua0sb                                       2.0   \n",
+       "e5ua84v                                       3.0   \n",
        "\n",
-       "         prop-nonzero[indegree over c->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.666667       \n",
-       "e5ywqyk                                           0.777778       \n",
-       "e5qv9rj                                           0.444444       \n",
-       "e6jhojf                                           0.777778       \n",
-       "e6989ii                                           0.777778       \n",
-       "e69lgse                                           0.444444       \n",
-       "e5kwkg2                                           0.555556       \n",
-       "e6mehe7                                           0.555556       \n",
-       "e6m0hsd                                           0.777778       \n",
-       "e64r385                                           0.555556       \n",
-       "e5surbt                                           0.444444       \n",
-       "e58gxii                                           0.555556       \n",
-       "e64vc8y                                           0.333333       \n",
-       "e57504g                                           0.555556       \n",
-       "e5borjq                                           0.444444       \n",
-       "e64n9zv                                           0.777778       \n",
-       "e582ud3                                           0.222222       \n",
-       "e64i9cf                                           0.444444       \n",
-       "e6q9204                                           0.666667       \n",
-       "e5modd7                                           0.333333       \n",
-       "e5xhbyd                                           0.666667       \n",
-       "e5oaf7h                                           0.666667       \n",
-       "e6nir3u                                           0.777778       \n",
-       "e6c3xdn                                           0.777778       \n",
-       "e5d3zaa                                           0.555556       \n",
-       "e5gnjv9                                           0.111111       \n",
-       "e69gw2t                                           0.555556       \n",
-       "e5syrih                                           0.555556       \n",
-       "e5sa2yf                                           0.888889       \n",
-       "e6ai7z5                                           0.666667       \n",
-       "...                                                    ...       \n",
-       "e5smhzk                                           0.777778       \n",
-       "e5v91s0                                           0.333333       \n",
-       "e6n6di6                                           0.555556       \n",
-       "e6iqq30                                           0.333333       \n",
-       "e5bfad7                                           0.444444       \n",
-       "e6x5he5                                           0.444444       \n",
-       "e6l9uyf                                           0.333333       \n",
-       "e57hyr1                                           0.444444       \n",
-       "e5b8sj7                                           0.333333       \n",
-       "e6nlep7                                           0.000000       \n",
-       "e6ltazd                                           0.555556       \n",
-       "e57a6qq                                           0.666667       \n",
-       "e5qc7eb                                           0.444444       \n",
-       "e6hqt5y                                           0.222222       \n",
-       "e5ua84v                                           0.555556       \n",
-       "e65m7kq                                           0.444444       \n",
-       "e5ggtru                                           0.444444       \n",
-       "e5pmmig                                           0.777778       \n",
-       "e64l6vq                                           0.555556       \n",
-       "e6fjx0d                                           0.777778       \n",
-       "e5h3xyy                                           0.444444       \n",
-       "e589ri5                                           0.333333       \n",
-       "e5beuqa                                           0.555556       \n",
-       "e5lqoj1                                           0.444444       \n",
-       "e5kvch1                                           0.666667       \n",
-       "e6srvwm                                           0.444444       \n",
-       "e5o65mk                                           0.777778       \n",
-       "e647cm8                                           0.333333       \n",
-       "e58n526                                           0.000000       \n",
-       "e69r2kg                                           0.555556       \n",
+       "         is-present[external reciprocity motif over mid-thread]  \\\n",
+       "e5hm9mp                                                1.0        \n",
+       "e5ytz1d                                                0.0        \n",
+       "e6ls80j                                                1.0        \n",
+       "e5mhgl5                                                1.0        \n",
+       "e6w6fah                                                0.0        \n",
+       "...                                                    ...        \n",
+       "e65ca8k                                                0.0        \n",
+       "e6cdkpy                                                1.0        \n",
+       "e5wc4tj                                                0.0        \n",
+       "e6ua0sb                                                1.0        \n",
+       "e5ua84v                                                1.0        \n",
        "\n",
-       "         prop-nonzero[indegree over c->c responses]  \\\n",
-       "e6p7yrp                                         0.7   \n",
-       "e5ywqyk                                         0.8   \n",
-       "e5qv9rj                                         0.5   \n",
-       "e6jhojf                                         0.8   \n",
-       "e6989ii                                         0.8   \n",
-       "e69lgse                                         0.5   \n",
-       "e5kwkg2                                         0.6   \n",
-       "e6mehe7                                         0.6   \n",
-       "e6m0hsd                                         0.8   \n",
-       "e64r385                                         0.6   \n",
-       "e5surbt                                         0.5   \n",
-       "e58gxii                                         0.6   \n",
-       "e64vc8y                                         0.4   \n",
-       "e57504g                                         0.6   \n",
-       "e5borjq                                         0.5   \n",
-       "e64n9zv                                         0.8   \n",
-       "e582ud3                                         0.3   \n",
-       "e64i9cf                                         0.5   \n",
-       "e6q9204                                         0.7   \n",
-       "e5modd7                                         0.4   \n",
-       "e5xhbyd                                         0.7   \n",
-       "e5oaf7h                                         0.7   \n",
-       "e6nir3u                                         0.8   \n",
-       "e6c3xdn                                         0.8   \n",
-       "e5d3zaa                                         0.6   \n",
-       "e5gnjv9                                         0.2   \n",
-       "e69gw2t                                         0.6   \n",
-       "e5syrih                                         0.6   \n",
-       "e5sa2yf                                         0.9   \n",
-       "e6ai7z5                                         0.7   \n",
-       "...                                             ...   \n",
-       "e5smhzk                                         0.8   \n",
-       "e5v91s0                                         0.4   \n",
-       "e6n6di6                                         0.6   \n",
-       "e6iqq30                                         0.4   \n",
-       "e5bfad7                                         0.5   \n",
-       "e6x5he5                                         0.5   \n",
-       "e6l9uyf                                         0.4   \n",
-       "e57hyr1                                         0.5   \n",
-       "e5b8sj7                                         0.4   \n",
-       "e6nlep7                                         0.1   \n",
-       "e6ltazd                                         0.6   \n",
-       "e57a6qq                                         0.7   \n",
-       "e5qc7eb                                         0.5   \n",
-       "e6hqt5y                                         0.3   \n",
-       "e5ua84v                                         0.6   \n",
-       "e65m7kq                                         0.5   \n",
-       "e5ggtru                                         0.5   \n",
-       "e5pmmig                                         0.8   \n",
-       "e64l6vq                                         0.6   \n",
-       "e6fjx0d                                         0.8   \n",
-       "e5h3xyy                                         0.5   \n",
-       "e589ri5                                         0.4   \n",
-       "e5beuqa                                         0.6   \n",
-       "e5lqoj1                                         0.5   \n",
-       "e5kvch1                                         0.7   \n",
-       "e6srvwm                                         0.5   \n",
-       "e5o65mk                                         0.8   \n",
-       "e647cm8                                         0.4   \n",
-       "e58n526                                         0.1   \n",
-       "e69r2kg                                         0.6   \n",
+       "         count[external reciprocity motif over mid-thread]  \\\n",
+       "e5hm9mp                                                2.0   \n",
+       "e5ytz1d                                                0.0   \n",
+       "e6ls80j                                                1.0   \n",
+       "e5mhgl5                                                4.0   \n",
+       "e6w6fah                                                0.0   \n",
+       "...                                                    ...   \n",
+       "e65ca8k                                                0.0   \n",
+       "e6cdkpy                                                1.0   \n",
+       "e5wc4tj                                                0.0   \n",
+       "e6ua0sb                                                4.0   \n",
+       "e5ua84v                                                2.0   \n",
        "\n",
-       "         prop-nonzero[outdegree over C->C mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.666667        \n",
-       "e5ywqyk                                           0.750000        \n",
-       "e5qv9rj                                           0.666667        \n",
-       "e6jhojf                                           0.800000        \n",
-       "e6989ii                                           1.000000        \n",
-       "e69lgse                                           0.714286        \n",
-       "e5kwkg2                                           0.666667        \n",
-       "e6mehe7                                           0.500000        \n",
-       "e6m0hsd                                           1.000000        \n",
-       "e64r385                                           0.857143        \n",
-       "e5surbt                                           0.444444        \n",
-       "e58gxii                                           0.833333        \n",
-       "e64vc8y                                           0.333333        \n",
-       "e57504g                                           0.857143        \n",
-       "e5borjq                                           0.875000        \n",
-       "e64n9zv                                           1.000000        \n",
-       "e582ud3                                           0.333333        \n",
-       "e64i9cf                                           0.500000        \n",
-       "e6q9204                                           1.000000        \n",
-       "e5modd7                                           0.888889        \n",
-       "e5xhbyd                                           1.000000        \n",
-       "e5oaf7h                                           1.000000        \n",
-       "e6nir3u                                           1.000000        \n",
-       "e6c3xdn                                           0.888889        \n",
-       "e5d3zaa                                           0.833333        \n",
-       "e5gnjv9                                           0.125000        \n",
-       "e69gw2t                                           0.800000        \n",
-       "e5syrih                                           1.000000        \n",
-       "e5sa2yf                                           1.000000        \n",
-       "e6ai7z5                                           0.600000        \n",
-       "...                                                    ...        \n",
-       "e5smhzk                                           0.666667        \n",
-       "e5v91s0                                           0.444444        \n",
-       "e6n6di6                                           0.875000        \n",
-       "e6iqq30                                           0.333333        \n",
-       "e5bfad7                                           0.625000        \n",
-       "e6x5he5                                           0.200000        \n",
-       "e6l9uyf                                           0.500000        \n",
-       "e57hyr1                                           0.833333        \n",
-       "e5b8sj7                                           0.750000        \n",
-       "e6nlep7                                           0.000000        \n",
-       "e6ltazd                                           1.000000        \n",
-       "e57a6qq                                           1.000000        \n",
-       "e5qc7eb                                           1.000000        \n",
-       "e6hqt5y                                           0.625000        \n",
-       "e5ua84v                                           1.000000        \n",
-       "e65m7kq                                           0.625000        \n",
-       "e5ggtru                                           1.000000        \n",
-       "e5pmmig                                           1.000000        \n",
-       "e64l6vq                                           0.666667        \n",
-       "e6fjx0d                                           0.666667        \n",
-       "e5h3xyy                                           0.625000        \n",
-       "e589ri5                                           0.333333        \n",
-       "e5beuqa                                           1.000000        \n",
-       "e5lqoj1                                           0.333333        \n",
-       "e5kvch1                                           0.833333        \n",
-       "e6srvwm                                           0.750000        \n",
-       "e5o65mk                                           1.000000        \n",
-       "e647cm8                                           0.555556        \n",
-       "e58n526                                           0.000000        \n",
-       "e69r2kg                                           0.750000        \n",
+       "         is-present[dyadic interaction motif over mid-thread]  \\\n",
+       "e5hm9mp                                                1.0      \n",
+       "e5ytz1d                                                0.0      \n",
+       "e6ls80j                                                1.0      \n",
+       "e5mhgl5                                                1.0      \n",
+       "e6w6fah                                                0.0      \n",
+       "...                                                    ...      \n",
+       "e65ca8k                                                0.0      \n",
+       "e6cdkpy                                                0.0      \n",
+       "e5wc4tj                                                1.0      \n",
+       "e6ua0sb                                                1.0      \n",
+       "e5ua84v                                                1.0      \n",
        "\n",
-       "         prop-nonzero[outdegree over C->C responses]  \\\n",
-       "e6p7yrp                                     1.000000   \n",
-       "e5ywqyk                                     1.000000   \n",
-       "e5qv9rj                                     0.900000   \n",
-       "e6jhojf                                     1.000000   \n",
-       "e6989ii                                     1.000000   \n",
-       "e69lgse                                     1.000000   \n",
-       "e5kwkg2                                     0.900000   \n",
-       "e6mehe7                                     1.000000   \n",
-       "e6m0hsd                                     1.000000   \n",
-       "e64r385                                     0.875000   \n",
-       "e5surbt                                     0.900000   \n",
-       "e58gxii                                     1.000000   \n",
-       "e64vc8y                                     0.900000   \n",
-       "e57504g                                     0.875000   \n",
-       "e5borjq                                     1.000000   \n",
-       "e64n9zv                                     1.000000   \n",
-       "e582ud3                                     0.900000   \n",
-       "e64i9cf                                     1.000000   \n",
-       "e6q9204                                     0.833333   \n",
-       "e5modd7                                     0.900000   \n",
-       "e5xhbyd                                     1.000000   \n",
-       "e5oaf7h                                     1.000000   \n",
-       "e6nir3u                                     1.000000   \n",
-       "e6c3xdn                                     0.900000   \n",
-       "e5d3zaa                                     0.857143   \n",
-       "e5gnjv9                                     0.888889   \n",
-       "e69gw2t                                     1.000000   \n",
-       "e5syrih                                     1.000000   \n",
-       "e5sa2yf                                     1.000000   \n",
-       "e6ai7z5                                     1.000000   \n",
+       "         count[dyadic interaction motif over mid-thread]  \\\n",
+       "e5hm9mp                                              2.0   \n",
+       "e5ytz1d                                              0.0   \n",
+       "e6ls80j                                              1.0   \n",
+       "e5mhgl5                                              1.0   \n",
+       "e6w6fah                                              0.0   \n",
+       "...                                                  ...   \n",
+       "e65ca8k                                              0.0   \n",
+       "e6cdkpy                                              0.0   \n",
+       "e5wc4tj                                              1.0   \n",
+       "e6ua0sb                                              2.0   \n",
+       "e5ua84v                                              3.0   \n",
+       "\n",
+       "         is-present[incoming triads over mid-thread]  \\\n",
+       "e5hm9mp                                          1.0   \n",
+       "e5ytz1d                                          1.0   \n",
+       "e6ls80j                                          1.0   \n",
+       "e5mhgl5                                          1.0   \n",
+       "e6w6fah                                          0.0   \n",
        "...                                              ...   \n",
-       "e5smhzk                                     1.000000   \n",
-       "e5v91s0                                     0.900000   \n",
-       "e6n6di6                                     0.888889   \n",
-       "e6iqq30                                     1.000000   \n",
-       "e5bfad7                                     1.000000   \n",
-       "e6x5he5                                     1.000000   \n",
-       "e6l9uyf                                     0.888889   \n",
-       "e57hyr1                                     0.857143   \n",
-       "e5b8sj7                                     1.000000   \n",
-       "e6nlep7                                     0.900000   \n",
-       "e6ltazd                                     0.833333   \n",
-       "e57a6qq                                     1.000000   \n",
-       "e5qc7eb                                     1.000000   \n",
-       "e6hqt5y                                     0.888889   \n",
-       "e5ua84v                                     0.857143   \n",
-       "e65m7kq                                     0.888889   \n",
-       "e5ggtru                                     0.888889   \n",
-       "e5pmmig                                     0.800000   \n",
-       "e64l6vq                                     1.000000   \n",
-       "e6fjx0d                                     0.750000   \n",
-       "e5h3xyy                                     0.888889   \n",
-       "e589ri5                                     0.900000   \n",
-       "e5beuqa                                     0.833333   \n",
-       "e5lqoj1                                     0.857143   \n",
-       "e5kvch1                                     0.857143   \n",
-       "e6srvwm                                     0.888889   \n",
-       "e5o65mk                                     1.000000   \n",
-       "e647cm8                                     1.000000   \n",
-       "e58n526                                     0.900000   \n",
-       "e69r2kg                                     1.000000   \n",
+       "e65ca8k                                          0.0   \n",
+       "e6cdkpy                                          1.0   \n",
+       "e5wc4tj                                          0.0   \n",
+       "e6ua0sb                                          1.0   \n",
+       "e5ua84v                                          1.0   \n",
        "\n",
-       "         prop-nonzero[outdegree over C->c mid-thread responses]  \\\n",
-       "e6p7yrp                                           0.666667        \n",
-       "e5ywqyk                                           0.750000        \n",
-       "e5qv9rj                                           0.666667        \n",
-       "e6jhojf                                           0.800000        \n",
-       "e6989ii                                           1.000000        \n",
-       "e69lgse                                           0.714286        \n",
-       "e5kwkg2                                           0.666667        \n",
-       "e6mehe7                                           0.500000        \n",
-       "e6m0hsd                                           1.000000        \n",
-       "e64r385                                           0.857143        \n",
-       "e5surbt                                           0.444444        \n",
-       "e58gxii                                           0.833333        \n",
-       "e64vc8y                                           0.333333        \n",
-       "e57504g                                           0.857143        \n",
-       "e5borjq                                           0.875000        \n",
-       "e64n9zv                                           1.000000        \n",
-       "e582ud3                                           0.333333        \n",
-       "e64i9cf                                           0.500000        \n",
-       "e6q9204                                           1.000000        \n",
-       "e5modd7                                           0.888889        \n",
-       "e5xhbyd                                           1.000000        \n",
-       "e5oaf7h                                           1.000000        \n",
-       "e6nir3u                                           1.000000        \n",
-       "e6c3xdn                                           0.888889        \n",
-       "e5d3zaa                                           0.833333        \n",
-       "e5gnjv9                                           0.125000        \n",
-       "e69gw2t                                           0.800000        \n",
-       "e5syrih                                           1.000000        \n",
-       "e5sa2yf                                           1.000000        \n",
-       "e6ai7z5                                           0.600000        \n",
-       "...                                                    ...        \n",
-       "e5smhzk                                           0.666667        \n",
-       "e5v91s0                                           0.444444        \n",
-       "e6n6di6                                           0.875000        \n",
-       "e6iqq30                                           0.333333        \n",
-       "e5bfad7                                           0.625000        \n",
-       "e6x5he5                                           0.200000        \n",
-       "e6l9uyf                                           0.500000        \n",
-       "e57hyr1                                           0.833333        \n",
-       "e5b8sj7                                           0.750000        \n",
-       "e6nlep7                                           0.000000        \n",
-       "e6ltazd                                           1.000000        \n",
-       "e57a6qq                                           1.000000        \n",
-       "e5qc7eb                                           1.000000        \n",
-       "e6hqt5y                                           0.625000        \n",
-       "e5ua84v                                           1.000000        \n",
-       "e65m7kq                                           0.625000        \n",
-       "e5ggtru                                           1.000000        \n",
-       "e5pmmig                                           1.000000        \n",
-       "e64l6vq                                           0.666667        \n",
-       "e6fjx0d                                           0.666667        \n",
-       "e5h3xyy                                           0.625000        \n",
-       "e589ri5                                           0.333333        \n",
-       "e5beuqa                                           1.000000        \n",
-       "e5lqoj1                                           0.333333        \n",
-       "e5kvch1                                           0.833333        \n",
-       "e6srvwm                                           0.750000        \n",
-       "e5o65mk                                           1.000000        \n",
-       "e647cm8                                           0.555556        \n",
-       "e58n526                                           0.000000        \n",
-       "e69r2kg                                           0.750000        \n",
-       "\n",
-       "         prop-nonzero[outdegree over C->c responses]  \n",
-       "e6p7yrp                                     1.000000  \n",
-       "e5ywqyk                                     1.000000  \n",
-       "e5qv9rj                                     0.900000  \n",
-       "e6jhojf                                     1.000000  \n",
-       "e6989ii                                     1.000000  \n",
-       "e69lgse                                     1.000000  \n",
-       "e5kwkg2                                     0.900000  \n",
-       "e6mehe7                                     1.000000  \n",
-       "e6m0hsd                                     1.000000  \n",
-       "e64r385                                     0.875000  \n",
-       "e5surbt                                     0.900000  \n",
-       "e58gxii                                     1.000000  \n",
-       "e64vc8y                                     0.900000  \n",
-       "e57504g                                     0.875000  \n",
-       "e5borjq                                     1.000000  \n",
-       "e64n9zv                                     1.000000  \n",
-       "e582ud3                                     0.900000  \n",
-       "e64i9cf                                     1.000000  \n",
-       "e6q9204                                     0.833333  \n",
-       "e5modd7                                     0.900000  \n",
-       "e5xhbyd                                     1.000000  \n",
-       "e5oaf7h                                     1.000000  \n",
-       "e6nir3u                                     1.000000  \n",
-       "e6c3xdn                                     0.900000  \n",
-       "e5d3zaa                                     0.857143  \n",
-       "e5gnjv9                                     0.888889  \n",
-       "e69gw2t                                     1.000000  \n",
-       "e5syrih                                     1.000000  \n",
-       "e5sa2yf                                     1.000000  \n",
-       "e6ai7z5                                     1.000000  \n",
-       "...                                              ...  \n",
-       "e5smhzk                                     1.000000  \n",
-       "e5v91s0                                     0.900000  \n",
-       "e6n6di6                                     0.888889  \n",
-       "e6iqq30                                     1.000000  \n",
-       "e5bfad7                                     1.000000  \n",
-       "e6x5he5                                     1.000000  \n",
-       "e6l9uyf                                     0.888889  \n",
-       "e57hyr1                                     0.857143  \n",
-       "e5b8sj7                                     1.000000  \n",
-       "e6nlep7                                     0.900000  \n",
-       "e6ltazd                                     0.833333  \n",
-       "e57a6qq                                     1.000000  \n",
-       "e5qc7eb                                     1.000000  \n",
-       "e6hqt5y                                     0.888889  \n",
-       "e5ua84v                                     0.857143  \n",
-       "e65m7kq                                     0.888889  \n",
-       "e5ggtru                                     0.888889  \n",
-       "e5pmmig                                     0.800000  \n",
-       "e64l6vq                                     1.000000  \n",
-       "e6fjx0d                                     0.750000  \n",
-       "e5h3xyy                                     0.888889  \n",
-       "e589ri5                                     0.900000  \n",
-       "e5beuqa                                     0.833333  \n",
-       "e5lqoj1                                     0.857143  \n",
-       "e5kvch1                                     0.857143  \n",
-       "e6srvwm                                     0.888889  \n",
-       "e5o65mk                                     1.000000  \n",
-       "e647cm8                                     1.000000  \n",
-       "e58n526                                     0.900000  \n",
-       "e69r2kg                                     1.000000  \n",
+       "         count[incoming triads over mid-thread]  \\\n",
+       "e5hm9mp                                     3.0   \n",
+       "e5ytz1d                                     4.0   \n",
+       "e6ls80j                                     3.0   \n",
+       "e5mhgl5                                     2.0   \n",
+       "e6w6fah                                     0.0   \n",
+       "...                                         ...   \n",
+       "e65ca8k                                     0.0   \n",
+       "e6cdkpy                                     2.0   \n",
+       "e5wc4tj                                     0.0   \n",
+       "e6ua0sb                                     6.0   \n",
+       "e5ua84v                                     7.0   \n",
+       "\n",
+       "         is-present[outgoing triads over mid-thread]  \\\n",
+       "e5hm9mp                                          1.0   \n",
+       "e5ytz1d                                          0.0   \n",
+       "e6ls80j                                          1.0   \n",
+       "e5mhgl5                                          1.0   \n",
+       "e6w6fah                                          0.0   \n",
+       "...                                              ...   \n",
+       "e65ca8k                                          0.0   \n",
+       "e6cdkpy                                          0.0   \n",
+       "e5wc4tj                                          0.0   \n",
+       "e6ua0sb                                          1.0   \n",
+       "e5ua84v                                          1.0   \n",
+       "\n",
+       "         count[outgoing triads over mid-thread]  \n",
+       "e5hm9mp                                     3.0  \n",
+       "e5ytz1d                                     0.0  \n",
+       "e6ls80j                                     1.0  \n",
+       "e5mhgl5                                     1.0  \n",
+       "e6w6fah                                     0.0  \n",
+       "...                                         ...  \n",
+       "e65ca8k                                     0.0  \n",
+       "e6cdkpy                                     0.0  \n",
+       "e5wc4tj                                     0.0  \n",
+       "e6ua0sb                                     2.0  \n",
+       "e5ua84v                                     2.0  \n",
        "\n",
        "[10000 rows x 140 columns]"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -18766,7 +4748,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18775,7 +4757,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18785,7 +4767,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18794,25 +4776,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['2nd-argmax[indegree over C->C mid-thread responses]',\n",
-       " '2nd-argmax[indegree over C->C responses]',\n",
-       " '2nd-argmax[indegree over C->c mid-thread responses]',\n",
-       " '2nd-argmax[indegree over C->c responses]',\n",
-       " '2nd-argmax[indegree over c->c mid-thread responses]',\n",
+       "['max[indegree over c->c responses]',\n",
+       " 'argmax[indegree over c->c responses]',\n",
+       " 'norm.max[indegree over c->c responses]',\n",
+       " '2nd-largest[indegree over c->c responses]',\n",
        " '2nd-argmax[indegree over c->c responses]',\n",
-       " '2nd-argmax[outdegree over C->C mid-thread responses]',\n",
-       " '2nd-argmax[outdegree over C->C responses]',\n",
-       " '2nd-argmax[outdegree over C->c mid-thread responses]',\n",
-       " '2nd-argmax[outdegree over C->c responses]']"
+       " 'norm.2nd-largest[indegree over c->c responses]',\n",
+       " 'mean[indegree over c->c responses]',\n",
+       " 'mean-nonzero[indegree over c->c responses]',\n",
+       " 'prop-nonzero[indegree over c->c responses]',\n",
+       " 'prop-multiple[indegree over c->c responses]']"
       ]
      },
-     "execution_count": 44,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -18830,7 +4812,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18841,27 +4823,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['2nd-argmax[indegree over C->C responses]',\n",
-       " '2nd-largest / max[indegree over C->C responses]',\n",
-       " '2nd-largest[indegree over C->C responses]',\n",
+       "['max[indegree over C->C responses]',\n",
        " 'argmax[indegree over C->C responses]',\n",
-       " 'entropy[indegree over C->C responses]',\n",
-       " 'max[indegree over C->C responses]',\n",
-       " 'mean-nonzero[indegree over C->C responses]',\n",
-       " 'mean[indegree over C->C responses]',\n",
-       " 'norm.2nd-largest[indegree over C->C responses]',\n",
        " 'norm.max[indegree over C->C responses]',\n",
+       " '2nd-largest[indegree over C->C responses]',\n",
+       " '2nd-argmax[indegree over C->C responses]',\n",
+       " 'norm.2nd-largest[indegree over C->C responses]',\n",
+       " 'mean[indegree over C->C responses]',\n",
+       " 'mean-nonzero[indegree over C->C responses]',\n",
+       " 'prop-nonzero[indegree over C->C responses]',\n",
        " 'prop-multiple[indegree over C->C responses]',\n",
-       " 'prop-nonzero[indegree over C->C responses]']"
+       " 'entropy[indegree over C->C responses]',\n",
+       " '2nd-largest / max[indegree over C->C responses]']"
       ]
      },
-     "execution_count": 48,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -18872,20 +4854,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['count[dyadic interaction motif]',\n",
+       "['count[reciprocity motif]',\n",
        " 'count[external reciprocity motif]',\n",
+       " 'count[dyadic interaction motif]',\n",
        " 'count[incoming triads]',\n",
-       " 'count[outgoing triads]',\n",
-       " 'count[reciprocity motif]']"
+       " 'count[outgoing triads]']"
       ]
      },
-     "execution_count": 49,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -18907,7 +4889,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 29,
    "metadata": {
     "scrolled": true
    },
@@ -19018,7 +5000,7 @@
        "prop-nonzero[indegree over C->C responses]       0.666667  1.000000"
       ]
      },
-     "execution_count": 51,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -19036,7 +5018,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
@@ -19145,7 +5127,7 @@
        "prop-nonzero[outdegree over C->C mid-thread res...  0.833333  1.000000"
       ]
      },
-     "execution_count": 52,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -19163,7 +5145,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -19230,7 +5212,7 @@
        "count[reciprocity motif]               3.0      8.0"
       ]
      },
-     "execution_count": 53,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -19248,7 +5230,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19261,7 +5243,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19271,7 +5253,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19284,7 +5266,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19303,7 +5285,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -19382,7 +5364,7 @@
        "6 -0.605281  0.017527"
       ]
      },
-     "execution_count": 59,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -19400,7 +5382,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -19428,41 +5410,21 @@
        "      <th>1</th>\n",
        "      <th>2</th>\n",
        "      <th>3</th>\n",
-       "      <th>4</th>\n",
-       "      <th>5</th>\n",
-       "      <th>6</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2nd-argmax[indegree over C-&gt;C responses]</th>\n",
-       "      <td>0.139340</td>\n",
-       "      <td>0.113322</td>\n",
-       "      <td>0.106261</td>\n",
-       "      <td>-0.316196</td>\n",
-       "      <td>0.261848</td>\n",
-       "      <td>0.887307</td>\n",
-       "      <td>-0.024356</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2nd-largest / max[indegree over C-&gt;C responses]</th>\n",
-       "      <td>-0.189063</td>\n",
-       "      <td>-0.433123</td>\n",
-       "      <td>-0.472973</td>\n",
-       "      <td>-0.252028</td>\n",
-       "      <td>0.338874</td>\n",
-       "      <td>0.598865</td>\n",
-       "      <td>0.126351</td>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
        "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
        "    <tr>\n",
-       "      <th>2nd-largest[indegree over C-&gt;C responses]</th>\n",
-       "      <td>0.264775</td>\n",
-       "      <td>-0.595095</td>\n",
-       "      <td>-0.177363</td>\n",
-       "      <td>-0.032607</td>\n",
-       "      <td>0.369844</td>\n",
-       "      <td>0.636419</td>\n",
-       "      <td>0.037712</td>\n",
+       "      <th>max[indegree over C-&gt;C responses]</th>\n",
+       "      <td>0.574040</td>\n",
+       "      <td>0.331249</td>\n",
+       "      <td>0.451891</td>\n",
+       "      <td>0.298591</td>\n",
+       "      <td>-0.098847</td>\n",
+       "      <td>-0.345627</td>\n",
+       "      <td>-0.371700</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>argmax[indegree over C-&gt;C responses]</th>\n",
@@ -19475,34 +5437,44 @@
        "      <td>0.001900</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>entropy[indegree over C-&gt;C responses]</th>\n",
-       "      <td>-0.001602</td>\n",
-       "      <td>-0.493754</td>\n",
-       "      <td>0.383985</td>\n",
-       "      <td>-0.657503</td>\n",
-       "      <td>-0.376240</td>\n",
-       "      <td>0.178189</td>\n",
-       "      <td>0.056053</td>\n",
+       "      <th>norm.max[indegree over C-&gt;C responses]</th>\n",
+       "      <td>0.136265</td>\n",
+       "      <td>0.633611</td>\n",
+       "      <td>-0.054505</td>\n",
+       "      <td>0.660700</td>\n",
+       "      <td>0.089491</td>\n",
+       "      <td>-0.360409</td>\n",
+       "      <td>-0.050698</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>max[indegree over C-&gt;C responses]</th>\n",
-       "      <td>0.574040</td>\n",
-       "      <td>0.331249</td>\n",
-       "      <td>0.451891</td>\n",
-       "      <td>0.298591</td>\n",
-       "      <td>-0.098847</td>\n",
-       "      <td>-0.345627</td>\n",
-       "      <td>-0.371700</td>\n",
+       "      <th>2nd-largest[indegree over C-&gt;C responses]</th>\n",
+       "      <td>0.264775</td>\n",
+       "      <td>-0.595095</td>\n",
+       "      <td>-0.177363</td>\n",
+       "      <td>-0.032607</td>\n",
+       "      <td>0.369844</td>\n",
+       "      <td>0.636419</td>\n",
+       "      <td>0.037712</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>mean-nonzero[indegree over C-&gt;C responses]</th>\n",
-       "      <td>0.561474</td>\n",
-       "      <td>0.246293</td>\n",
-       "      <td>0.073209</td>\n",
-       "      <td>0.492266</td>\n",
-       "      <td>0.272666</td>\n",
-       "      <td>-0.249315</td>\n",
-       "      <td>-0.489793</td>\n",
+       "      <th>2nd-argmax[indegree over C-&gt;C responses]</th>\n",
+       "      <td>0.139340</td>\n",
+       "      <td>0.113322</td>\n",
+       "      <td>0.106261</td>\n",
+       "      <td>-0.316196</td>\n",
+       "      <td>0.261848</td>\n",
+       "      <td>0.887307</td>\n",
+       "      <td>-0.024356</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>norm.2nd-largest[indegree over C-&gt;C responses]</th>\n",
+       "      <td>-0.206815</td>\n",
+       "      <td>-0.210187</td>\n",
+       "      <td>-0.667660</td>\n",
+       "      <td>0.126509</td>\n",
+       "      <td>0.418324</td>\n",
+       "      <td>0.523214</td>\n",
+       "      <td>0.050272</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean[indegree over C-&gt;C responses]</th>\n",
@@ -19515,24 +5487,24 @@
        "      <td>-0.522766</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>norm.2nd-largest[indegree over C-&gt;C responses]</th>\n",
-       "      <td>-0.206815</td>\n",
-       "      <td>-0.210187</td>\n",
-       "      <td>-0.667660</td>\n",
-       "      <td>0.126509</td>\n",
-       "      <td>0.418324</td>\n",
-       "      <td>0.523214</td>\n",
-       "      <td>0.050272</td>\n",
+       "      <th>mean-nonzero[indegree over C-&gt;C responses]</th>\n",
+       "      <td>0.561474</td>\n",
+       "      <td>0.246293</td>\n",
+       "      <td>0.073209</td>\n",
+       "      <td>0.492266</td>\n",
+       "      <td>0.272666</td>\n",
+       "      <td>-0.249315</td>\n",
+       "      <td>-0.489793</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>norm.max[indegree over C-&gt;C responses]</th>\n",
-       "      <td>0.136265</td>\n",
-       "      <td>0.633611</td>\n",
-       "      <td>-0.054505</td>\n",
-       "      <td>0.660700</td>\n",
-       "      <td>0.089491</td>\n",
-       "      <td>-0.360409</td>\n",
-       "      <td>-0.050698</td>\n",
+       "      <th>prop-nonzero[indegree over C-&gt;C responses]</th>\n",
+       "      <td>-0.945359</td>\n",
+       "      <td>-0.101535</td>\n",
+       "      <td>0.238357</td>\n",
+       "      <td>-0.078078</td>\n",
+       "      <td>-0.107471</td>\n",
+       "      <td>0.146344</td>\n",
+       "      <td>-0.010486</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>prop-multiple[indegree over C-&gt;C responses]</th>\n",
@@ -19545,14 +5517,24 @@
        "      <td>-0.415719</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>prop-nonzero[indegree over C-&gt;C responses]</th>\n",
-       "      <td>-0.945359</td>\n",
-       "      <td>-0.101535</td>\n",
-       "      <td>0.238357</td>\n",
-       "      <td>-0.078078</td>\n",
-       "      <td>-0.107471</td>\n",
-       "      <td>0.146344</td>\n",
-       "      <td>-0.010486</td>\n",
+       "      <th>entropy[indegree over C-&gt;C responses]</th>\n",
+       "      <td>-0.001602</td>\n",
+       "      <td>-0.493754</td>\n",
+       "      <td>0.383985</td>\n",
+       "      <td>-0.657503</td>\n",
+       "      <td>-0.376240</td>\n",
+       "      <td>0.178189</td>\n",
+       "      <td>0.056053</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2nd-largest / max[indegree over C-&gt;C responses]</th>\n",
+       "      <td>-0.189063</td>\n",
+       "      <td>-0.433123</td>\n",
+       "      <td>-0.472973</td>\n",
+       "      <td>-0.252028</td>\n",
+       "      <td>0.338874</td>\n",
+       "      <td>0.598865</td>\n",
+       "      <td>0.126351</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -19560,49 +5542,49 @@
       ],
       "text/plain": [
        "                                                        0         1         2  \\\n",
-       "2nd-argmax[indegree over C->C responses]         0.139340  0.113322  0.106261   \n",
-       "2nd-largest / max[indegree over C->C responses] -0.189063 -0.433123 -0.472973   \n",
-       "2nd-largest[indegree over C->C responses]        0.264775 -0.595095 -0.177363   \n",
-       "argmax[indegree over C->C responses]             0.021994 -0.548696 -0.072024   \n",
-       "entropy[indegree over C->C responses]           -0.001602 -0.493754  0.383985   \n",
        "max[indegree over C->C responses]                0.574040  0.331249  0.451891   \n",
-       "mean-nonzero[indegree over C->C responses]       0.561474  0.246293  0.073209   \n",
-       "mean[indegree over C->C responses]              -0.303707 -0.230767  0.639219   \n",
-       "norm.2nd-largest[indegree over C->C responses]  -0.206815 -0.210187 -0.667660   \n",
+       "argmax[indegree over C->C responses]             0.021994 -0.548696 -0.072024   \n",
        "norm.max[indegree over C->C responses]           0.136265  0.633611 -0.054505   \n",
-       "prop-multiple[indegree over C->C responses]      0.355365 -0.438412 -0.063833   \n",
+       "2nd-largest[indegree over C->C responses]        0.264775 -0.595095 -0.177363   \n",
+       "2nd-argmax[indegree over C->C responses]         0.139340  0.113322  0.106261   \n",
+       "norm.2nd-largest[indegree over C->C responses]  -0.206815 -0.210187 -0.667660   \n",
+       "mean[indegree over C->C responses]              -0.303707 -0.230767  0.639219   \n",
+       "mean-nonzero[indegree over C->C responses]       0.561474  0.246293  0.073209   \n",
        "prop-nonzero[indegree over C->C responses]      -0.945359 -0.101535  0.238357   \n",
+       "prop-multiple[indegree over C->C responses]      0.355365 -0.438412 -0.063833   \n",
+       "entropy[indegree over C->C responses]           -0.001602 -0.493754  0.383985   \n",
+       "2nd-largest / max[indegree over C->C responses] -0.189063 -0.433123 -0.472973   \n",
        "\n",
        "                                                        3         4         5  \\\n",
-       "2nd-argmax[indegree over C->C responses]        -0.316196  0.261848  0.887307   \n",
-       "2nd-largest / max[indegree over C->C responses] -0.252028  0.338874  0.598865   \n",
-       "2nd-largest[indegree over C->C responses]       -0.032607  0.369844  0.636419   \n",
-       "argmax[indegree over C->C responses]             0.348774 -0.487366 -0.578004   \n",
-       "entropy[indegree over C->C responses]           -0.657503 -0.376240  0.178189   \n",
        "max[indegree over C->C responses]                0.298591 -0.098847 -0.345627   \n",
-       "mean-nonzero[indegree over C->C responses]       0.492266  0.272666 -0.249315   \n",
-       "mean[indegree over C->C responses]               0.266533  0.317526 -0.027597   \n",
-       "norm.2nd-largest[indegree over C->C responses]   0.126509  0.418324  0.523214   \n",
+       "argmax[indegree over C->C responses]             0.348774 -0.487366 -0.578004   \n",
        "norm.max[indegree over C->C responses]           0.660700  0.089491 -0.360409   \n",
-       "prop-multiple[indegree over C->C responses]      0.156168  0.692934 -0.008221   \n",
+       "2nd-largest[indegree over C->C responses]       -0.032607  0.369844  0.636419   \n",
+       "2nd-argmax[indegree over C->C responses]        -0.316196  0.261848  0.887307   \n",
+       "norm.2nd-largest[indegree over C->C responses]   0.126509  0.418324  0.523214   \n",
+       "mean[indegree over C->C responses]               0.266533  0.317526 -0.027597   \n",
+       "mean-nonzero[indegree over C->C responses]       0.492266  0.272666 -0.249315   \n",
        "prop-nonzero[indegree over C->C responses]      -0.078078 -0.107471  0.146344   \n",
+       "prop-multiple[indegree over C->C responses]      0.156168  0.692934 -0.008221   \n",
+       "entropy[indegree over C->C responses]           -0.657503 -0.376240  0.178189   \n",
+       "2nd-largest / max[indegree over C->C responses] -0.252028  0.338874  0.598865   \n",
        "\n",
        "                                                        6  \n",
-       "2nd-argmax[indegree over C->C responses]        -0.024356  \n",
-       "2nd-largest / max[indegree over C->C responses]  0.126351  \n",
-       "2nd-largest[indegree over C->C responses]        0.037712  \n",
-       "argmax[indegree over C->C responses]             0.001900  \n",
-       "entropy[indegree over C->C responses]            0.056053  \n",
        "max[indegree over C->C responses]               -0.371700  \n",
-       "mean-nonzero[indegree over C->C responses]      -0.489793  \n",
-       "mean[indegree over C->C responses]              -0.522766  \n",
-       "norm.2nd-largest[indegree over C->C responses]   0.050272  \n",
+       "argmax[indegree over C->C responses]             0.001900  \n",
        "norm.max[indegree over C->C responses]          -0.050698  \n",
+       "2nd-largest[indegree over C->C responses]        0.037712  \n",
+       "2nd-argmax[indegree over C->C responses]        -0.024356  \n",
+       "norm.2nd-largest[indegree over C->C responses]   0.050272  \n",
+       "mean[indegree over C->C responses]              -0.522766  \n",
+       "mean-nonzero[indegree over C->C responses]      -0.489793  \n",
+       "prop-nonzero[indegree over C->C responses]      -0.010486  \n",
        "prop-multiple[indegree over C->C responses]     -0.415719  \n",
-       "prop-nonzero[indegree over C->C responses]      -0.010486  "
+       "entropy[indegree over C->C responses]            0.056053  \n",
+       "2nd-largest / max[indegree over C->C responses]  0.126351  "
       ]
      },
-     "execution_count": 60,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -19620,7 +5602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19629,7 +5611,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
@@ -19638,7 +5620,7 @@
        "10000"
       ]
      },
-     "execution_count": 63,
+     "execution_count": 39,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -19649,7 +5631,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19658,7 +5640,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19671,7 +5653,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
@@ -19787,7 +5769,7 @@
        "AskReddit     -0.316899  "
       ]
      },
-     "execution_count": 66,
+     "execution_count": 42,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -19805,7 +5787,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19816,21 +5798,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 44,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
-       "<Figure size 720x720 with 1 Axes>"
+       "<Figure size 1000x1000 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -19851,19 +5831,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": 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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -19925,7 +5903,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 46,
    "metadata": {
     "scrolled": true
    },
@@ -19942,7 +5920,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19959,7 +5937,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 48,
    "metadata": {
     "scrolled": true
    },
@@ -20117,7 +6095,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -20126,7 +6104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -20149,7 +6127,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [
     {
@@ -20185,7 +6163,7 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>e60kzm8</th>\n",
+       "      <th>e5q0p88</th>\n",
        "      <td>-0.963049</td>\n",
        "      <td>0.069720</td>\n",
        "      <td>0.012004</td>\n",
@@ -20193,10 +6171,10 @@
        "      <td>-0.253023</td>\n",
        "      <td>-0.035112</td>\n",
        "      <td>0.045334</td>\n",
-       "      <td>MensRights</td>\n",
+       "      <td>Christianity</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>e5q0p88</th>\n",
+       "      <th>e5d4yag</th>\n",
        "      <td>-0.963049</td>\n",
        "      <td>0.069720</td>\n",
        "      <td>0.012004</td>\n",
@@ -20207,7 +6185,7 @@
        "      <td>Christianity</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>e5d4yag</th>\n",
+       "      <th>e60kzm8</th>\n",
        "      <td>-0.963049</td>\n",
        "      <td>0.069720</td>\n",
        "      <td>0.012004</td>\n",
@@ -20215,7 +6193,7 @@
        "      <td>-0.253023</td>\n",
        "      <td>-0.035112</td>\n",
        "      <td>0.045334</td>\n",
-       "      <td>Christianity</td>\n",
+       "      <td>MensRights</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>e5m9w22</th>\n",
@@ -20240,7 +6218,7 @@
        "      <td>Music</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>e68nlvd</th>\n",
+       "      <th>e6r4v8m</th>\n",
        "      <td>-0.935494</td>\n",
        "      <td>0.050881</td>\n",
        "      <td>0.060026</td>\n",
@@ -20248,10 +6226,10 @@
        "      <td>-0.250417</td>\n",
        "      <td>-0.055384</td>\n",
        "      <td>0.220780</td>\n",
-       "      <td>Christianity</td>\n",
+       "      <td>POLITIC</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>e6r4v8m</th>\n",
+       "      <th>e5o4hip</th>\n",
        "      <td>-0.935494</td>\n",
        "      <td>0.050881</td>\n",
        "      <td>0.060026</td>\n",
@@ -20259,10 +6237,10 @@
        "      <td>-0.250417</td>\n",
        "      <td>-0.055384</td>\n",
        "      <td>0.220780</td>\n",
-       "      <td>POLITIC</td>\n",
+       "      <td>gonewild</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>e5ojhdr</th>\n",
+       "      <th>e68nlvd</th>\n",
        "      <td>-0.935494</td>\n",
        "      <td>0.050881</td>\n",
        "      <td>0.060026</td>\n",
@@ -20270,10 +6248,10 @@
        "      <td>-0.250417</td>\n",
        "      <td>-0.055384</td>\n",
        "      <td>0.220780</td>\n",
-       "      <td>AskMen</td>\n",
+       "      <td>Christianity</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>e5o4hip</th>\n",
+       "      <th>e5ojhdr</th>\n",
        "      <td>-0.935494</td>\n",
        "      <td>0.050881</td>\n",
        "      <td>0.060026</td>\n",
@@ -20281,7 +6259,7 @@
        "      <td>-0.250417</td>\n",
        "      <td>-0.055384</td>\n",
        "      <td>0.220780</td>\n",
-       "      <td>gonewild</td>\n",
+       "      <td>AskMen</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>e6jkkjw</th>\n",
@@ -20300,27 +6278,27 @@
       ],
       "text/plain": [
        "                0         1         2         3         4         5         6  \\\n",
-       "e60kzm8 -0.963049  0.069720  0.012004  0.014941 -0.253023 -0.035112  0.045334   \n",
        "e5q0p88 -0.963049  0.069720  0.012004  0.014941 -0.253023 -0.035112  0.045334   \n",
        "e5d4yag -0.963049  0.069720  0.012004  0.014941 -0.253023 -0.035112  0.045334   \n",
+       "e60kzm8 -0.963049  0.069720  0.012004  0.014941 -0.253023 -0.035112  0.045334   \n",
        "e5m9w22 -0.963049  0.069720  0.012004  0.014941 -0.253023 -0.035112  0.045334   \n",
        "e59g1nk -0.956579  0.050546 -0.028281  0.006982 -0.281819 -0.045649 -0.006813   \n",
-       "e68nlvd -0.935494  0.050881  0.060026  0.064334 -0.250417 -0.055384  0.220780   \n",
        "e6r4v8m -0.935494  0.050881  0.060026  0.064334 -0.250417 -0.055384  0.220780   \n",
-       "e5ojhdr -0.935494  0.050881  0.060026  0.064334 -0.250417 -0.055384  0.220780   \n",
        "e5o4hip -0.935494  0.050881  0.060026  0.064334 -0.250417 -0.055384  0.220780   \n",
+       "e68nlvd -0.935494  0.050881  0.060026  0.064334 -0.250417 -0.055384  0.220780   \n",
+       "e5ojhdr -0.935494  0.050881  0.060026  0.064334 -0.250417 -0.055384  0.220780   \n",
        "e6jkkjw -0.923477  0.027897  0.067691  0.035644 -0.276119 -0.062107  0.245887   \n",
        "\n",
        "            subreddit  \n",
-       "e60kzm8    MensRights  \n",
        "e5q0p88  Christianity  \n",
        "e5d4yag  Christianity  \n",
+       "e60kzm8    MensRights  \n",
        "e5m9w22       atheism  \n",
        "e59g1nk         Music  \n",
-       "e68nlvd  Christianity  \n",
        "e6r4v8m       POLITIC  \n",
-       "e5ojhdr        AskMen  \n",
        "e5o4hip      gonewild  \n",
+       "e68nlvd  Christianity  \n",
+       "e5ojhdr        AskMen  \n",
        "e6jkkjw       POLITIC  "
       ]
      },
@@ -20399,7 +6377,7 @@
        "      <td>-0.129918</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>prop-nonzero[indegree over C-&gt;c responses]</th>\n",
+       "      <th>prop-nonzero[indegree over c-&gt;c mid-thread responses]</th>\n",
        "      <td>-0.785073</td>\n",
        "      <td>-0.120033</td>\n",
        "      <td>-0.107805</td>\n",
@@ -20429,7 +6407,7 @@
        "      <td>0.042901</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>prop-nonzero[indegree over c-&gt;c mid-thread responses]</th>\n",
+       "      <th>prop-nonzero[indegree over C-&gt;c responses]</th>\n",
        "      <td>-0.785073</td>\n",
        "      <td>-0.120033</td>\n",
        "      <td>-0.107805</td>\n",
@@ -20468,10 +6446,10 @@
        "prop-nonzero[indegree over C->C responses]         -0.945359 -0.101535   \n",
        "count[reciprocity motif over mid-thread]           -0.809754  0.105072   \n",
        "count[reciprocity motif]                           -0.809152  0.173066   \n",
-       "prop-nonzero[indegree over C->c responses]         -0.785073 -0.120033   \n",
+       "prop-nonzero[indegree over c->c mid-thread resp... -0.785073 -0.120033   \n",
        "prop-nonzero[indegree over C->c mid-thread resp... -0.785073 -0.120033   \n",
        "prop-nonzero[indegree over c->c responses]         -0.785073 -0.120033   \n",
-       "prop-nonzero[indegree over c->c mid-thread resp... -0.785073 -0.120033   \n",
+       "prop-nonzero[indegree over C->c responses]         -0.785073 -0.120033   \n",
        "entropy[indegree over C->c responses]              -0.752376 -0.339732   \n",
        "is-present[reciprocity motif over mid-thread]      -0.746503 -0.388562   \n",
        "\n",
@@ -20480,10 +6458,10 @@
        "prop-nonzero[indegree over C->C responses]          0.238357 -0.078078   \n",
        "count[reciprocity motif over mid-thread]           -0.429701  0.326016   \n",
        "count[reciprocity motif]                           -0.206560  0.449086   \n",
-       "prop-nonzero[indegree over C->c responses]         -0.107805 -0.327275   \n",
+       "prop-nonzero[indegree over c->c mid-thread resp... -0.107805 -0.327275   \n",
        "prop-nonzero[indegree over C->c mid-thread resp... -0.107805 -0.327275   \n",
        "prop-nonzero[indegree over c->c responses]         -0.107805 -0.327275   \n",
-       "prop-nonzero[indegree over c->c mid-thread resp... -0.107805 -0.327275   \n",
+       "prop-nonzero[indegree over C->c responses]         -0.107805 -0.327275   \n",
        "entropy[indegree over C->c responses]              -0.136839 -0.383152   \n",
        "is-present[reciprocity motif over mid-thread]       0.299804  0.194661   \n",
        "\n",
@@ -20492,10 +6470,10 @@
        "prop-nonzero[indegree over C->C responses]         -0.107471  0.146344   \n",
        "count[reciprocity motif over mid-thread]            0.036748 -0.019626   \n",
        "count[reciprocity motif]                            0.224681 -0.060130   \n",
-       "prop-nonzero[indegree over C->c responses]         -0.495253  0.058358   \n",
+       "prop-nonzero[indegree over c->c mid-thread resp... -0.495253  0.058358   \n",
        "prop-nonzero[indegree over C->c mid-thread resp... -0.495253  0.058358   \n",
        "prop-nonzero[indegree over c->c responses]         -0.495253  0.058358   \n",
-       "prop-nonzero[indegree over c->c mid-thread resp... -0.495253  0.058358   \n",
+       "prop-nonzero[indegree over C->c responses]         -0.495253  0.058358   \n",
        "entropy[indegree over C->c responses]              -0.323822  0.136627   \n",
        "is-present[reciprocity motif over mid-thread]       0.101641 -0.001041   \n",
        "\n",
@@ -20504,10 +6482,10 @@
        "prop-nonzero[indegree over C->C responses]         -0.010486  \n",
        "count[reciprocity motif over mid-thread]           -0.201477  \n",
        "count[reciprocity motif]                           -0.129918  \n",
-       "prop-nonzero[indegree over C->c responses]          0.042901  \n",
+       "prop-nonzero[indegree over c->c mid-thread resp...  0.042901  \n",
        "prop-nonzero[indegree over C->c mid-thread resp...  0.042901  \n",
        "prop-nonzero[indegree over c->c responses]          0.042901  \n",
-       "prop-nonzero[indegree over c->c mid-thread resp...  0.042901  \n",
+       "prop-nonzero[indegree over C->c responses]          0.042901  \n",
        "entropy[indegree over C->c responses]               0.171623  \n",
        "is-present[reciprocity motif over mid-thread]      -0.391977  "
       ]
@@ -20727,7 +6705,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.9.0"
   }
  },
  "nbformat": 4,
diff --git a/examples/hyperconvo/predictive_tasks.ipynb b/examples/hyperconvo/predictive_tasks.ipynb
index 28259133..0edbc52a 100644
--- a/examples/hyperconvo/predictive_tasks.ipynb
+++ b/examples/hyperconvo/predictive_tasks.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -27,14 +27,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Dataset already exists at /Users/calebchiam/Documents/GitHub/ConvoKit/convokit/tensors/reddit-corpus-small\n"
+      "Dataset already exists at /Users/seanzhangkx/.convokit/downloads/reddit-corpus-small\n"
      ]
     }
    ],
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -62,7 +62,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -71,7 +71,7 @@
        "10000"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -82,11 +82,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
-    "threads_corpus = corpus.reindex_conversations(new_convo_roots=top_level_utterance_ids, \n",
+    "threads_corpus = corpus.reindex_conversations(source_corpus=corpus,\n",
+    "                                              new_convo_roots=top_level_utterance_ids, \n",
     "                                              preserve_convo_meta=True,\n",
     "                                              preserve_corpus_meta=False)"
    ]
@@ -119,7 +120,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -137,18 +138,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['2nd-argmax[indegree over C->C mid-thread responses]',\n",
-       " '2nd-argmax[indegree over C->C responses]',\n",
-       " '2nd-argmax[indegree over C->c mid-thread responses]']"
+       "['max[indegree over c->c responses]',\n",
+       " 'argmax[indegree over c->c responses]',\n",
+       " 'norm.max[indegree over c->c responses]']"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -166,7 +167,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -175,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -184,7 +185,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -193,7 +194,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -202,7 +203,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -220,13 +221,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
     "## volume is the number of unique users in the first 10 comments\n",
     "for convo in threads_corpus.iter_conversations():\n",
-    "    convo.meta['volume'] = len(set([utt.user for utt in convo.get_chronological_utterance_list()[:10]]))"
+    "    convo.meta['volume'] = len(set([utt.speaker for utt in convo.get_chronological_utterance_list()[:10]]))"
    ]
   },
   {
@@ -261,7 +262,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -279,28 +280,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'original_convo_meta': {'title': 'Daily Discussion, September 15, 2018',\n",
-       "  'num_comments': 97,\n",
-       "  'domain': 'self.Bitcoin',\n",
-       "  'timestamp': 1537002016,\n",
-       "  'subreddit': 'Bitcoin',\n",
-       "  'gilded': 0,\n",
-       "  'gildings': {'gid_1': 0, 'gid_2': 0, 'gid_3': 0},\n",
-       "  'stickied': False,\n",
-       "  'author_flair_text': ''},\n",
-       " 'original_convo_id': '9g03ho',\n",
-       " 'volume': 4,\n",
-       " 'comment-growth': True,\n",
-       " 'commenter-growth': True}"
+       "ConvoKitMeta({'original_convo_meta': {'title': 'Coming Soon: Sibling Rivalry Podcast Season 2 with Bob The Drag Queen &amp; Monét X Change', 'num_comments': 19, 'domain': 'youtube.com', 'timestamp': 1536033837, 'subreddit': 'rupaulsdragrace', 'gilded': 0, 'gildings': {'gid_1': 0, 'gid_2': 0, 'gid_3': 0}, 'stickied': False, 'author_flair_text': 'Miz Cracker'}, 'original_convo_id': '9cs8tg', 'volume': 6, 'comment-growth': False, 'commenter-growth': None})"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -318,7 +307,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -327,7 +316,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -343,16 +332,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<convokit.model.corpus.Corpus at 0x1344eeb10>"
+       "<convokit.model.corpus.Corpus at 0x7f7ea107b850>"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -363,7 +352,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -379,16 +368,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<convokit.model.corpus.Corpus at 0x1344eeb10>"
+       "<convokit.model.corpus.Corpus at 0x7f7ea107b850>"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -406,7 +395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -415,7 +404,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -428,10 +417,10 @@
     {
      "data": {
       "text/plain": [
-       "<convokit.model.corpus.Corpus at 0x1344eeb10>"
+       "<convokit.model.corpus.Corpus at 0x7f7ea107b850>"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -443,7 +432,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -456,10 +445,10 @@
     {
      "data": {
       "text/plain": [
-       "<convokit.model.corpus.Corpus at 0x1344eeb10>"
+       "<convokit.model.corpus.Corpus at 0x7f7ea107b850>"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -471,7 +460,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -480,7 +469,7 @@
        "{'bow_1', 'bow_2', 'hyperconvo', 'reply-tree'}"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -498,7 +487,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -537,7 +526,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -550,10 +539,10 @@
     {
      "data": {
       "text/plain": [
-       "0.5445037531276065"
+       "0.5774812343619683"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -577,7 +566,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -590,10 +579,10 @@
     {
      "data": {
       "text/plain": [
-       "0.5974145120934111"
+       "0.5973144286905754"
       ]
      },
-     "execution_count": 40,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -616,7 +605,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -629,10 +618,10 @@
     {
      "data": {
       "text/plain": [
-       "0.5955796497080901"
+       "0.5993327773144287"
       ]
      },
-     "execution_count": 41,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -656,7 +645,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -669,10 +658,10 @@
     {
      "data": {
       "text/plain": [
-       "0.8342285237698082"
+       "0.8160633861551293"
       ]
      },
-     "execution_count": 42,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -689,7 +678,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
@@ -702,10 +691,10 @@
     {
      "data": {
       "text/plain": [
-       "<convokit.paired_prediction.pairedVectorPrediction.PairedVectorPrediction at 0x14c1d3750>"
+       "<convokit.paired_prediction.pairedVectorPrediction.PairedVectorPrediction at 0x7f7e360f8820>"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -730,7 +719,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -743,10 +732,10 @@
     {
      "data": {
       "text/plain": [
-       "0.5815970386039133"
+       "0.5655737704918031"
       ]
      },
-     "execution_count": 43,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -770,7 +759,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
@@ -783,10 +772,10 @@
     {
      "data": {
       "text/plain": [
-       "0.509941829719725"
+       "0.5296668429402432"
       ]
      },
-     "execution_count": 44,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -809,7 +798,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -822,10 +811,10 @@
     {
      "data": {
       "text/plain": [
-       "0.5653622421998942"
+       "0.5849814912744579"
       ]
      },
-     "execution_count": 45,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -849,7 +838,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -862,10 +851,10 @@
     {
      "data": {
       "text/plain": [
-       "0.7154415653093601"
+       "0.7386567953463776"
       ]
      },
-     "execution_count": 46,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -897,7 +886,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.9.0"
   }
  },
  "nbformat": 4,
diff --git a/examples/merging/corpus_merge_demo.ipynb b/examples/merging/corpus_merge_demo.ipynb
index 25f212f1..0584f70d 100644
--- a/examples/merging/corpus_merge_demo.ipynb
+++ b/examples/merging/corpus_merge_demo.ipynb
@@ -119,12 +119,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[91mWARNING: \u001b[0mMultiple values found for Speaker(id: foxtrot, vectors: [], meta: {'yellow': 'food'}) for metadata key: 'yellow'. Taking the latest one found\n"
+      "\u001b[91mWARNING: \u001b[0mMultiple values found for Speaker(id: 'foxtrot', vectors: [], meta: ConvoKitMeta({'yellow': 'food'})) for metadata key: 'yellow'. Taking the latest one found\n"
      ]
     }
    ],
    "source": [
-    "corpus3 = corpus1.merge(corpus2)"
+    "corpus3 = Corpus.merge(corpus1, corpus2)"
    ]
   },
   {
@@ -168,7 +168,7 @@
     {
      "data": {
       "text/plain": [
-       "{'yellow': 'mood', 'hello': 'world'}"
+       "ConvoKitMeta({'yellow': 'mood', 'hello': 'world'})"
       ]
      },
      "execution_count": 8,
@@ -196,7 +196,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[Speaker({'obj_type': 'speaker', 'meta': {}, 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f16d0>, 'id': 'alice'}), Speaker({'obj_type': 'speaker', 'meta': {}, 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f16d0>, 'id': 'bob'}), Speaker({'obj_type': 'speaker', 'meta': {'yellow': 'mood', 'hello': 'world'}, 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f16d0>, 'id': 'foxtrot'}), Speaker({'obj_type': 'speaker', 'meta': {'what': 'a mood', 'hey': 'food'}, 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f16d0>, 'id': 'charlie'}), Speaker({'obj_type': 'speaker', 'meta': {}, 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f16d0>, 'id': 'echo'})]\n",
+      "[Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fd9924bfa90>, 'id': 'alice', 'meta': ConvoKitMeta({})}), Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fd9924bfa90>, 'id': 'bob', 'meta': ConvoKitMeta({})}), Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fd9924bfa90>, 'id': 'foxtrot', 'meta': ConvoKitMeta({'yellow': 'mood', 'hello': 'world'})}), Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fd9924bfa90>, 'id': 'charlie', 'meta': ConvoKitMeta({'what': 'a mood', 'hey': 'food'})}), Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fd9924bfa90>, 'id': 'echo', 'meta': ConvoKitMeta({})})]\n",
       "\n",
       "Number of Utterances: 1\n",
       "Number of Conversations: 1\n"
@@ -317,15 +317,15 @@
      "text": [
       "\u001b[91mWARNING: \u001b[0mFound conflicting values for Utterance '0' for metadata key: 'in'. Overwriting with other corpus's Utterance metadata.\n",
       "\u001b[91mWARNING: \u001b[0mUtterances with same id do not share the same data:\n",
-      "Utterance(id: '1', conversation_id: 0, reply-to: 0, speaker: Speaker(id: bob, vectors: [], meta: {}), timestamp: None, text: 'my name is bob', vectors: [], meta: {'fu': 'bu'})\n",
-      "Utterance(id: '1', conversation_id: 0, reply-to: 0, speaker: Speaker(id: bob, vectors: [], meta: {}), timestamp: None, text: 'my name is bobbb', vectors: [], meta: {'barrel': 'roll'})\n",
+      "Utterance(id: '1', conversation_id: 0, reply-to: 0, speaker: Speaker(id: 'bob', vectors: [], meta: ConvoKitMeta({})), timestamp: None, text: 'my name is bob', vectors: [], meta: ConvoKitMeta({'fu': 'bu'}))\n",
+      "Utterance(id: '1', conversation_id: 0, reply-to: 0, speaker: Speaker(id: 'bob', vectors: [], meta: ConvoKitMeta({})), timestamp: None, text: 'my name is bobbb', vectors: [], meta: ConvoKitMeta({'barrel': 'roll'}))\n",
       "Ignoring second corpus's utterance.\n",
-      "\u001b[91mWARNING: \u001b[0mFound conflicting values for Corpus metadata key: 'AB'. Overwriting with other Corpus's metadata.\n"
+      "\u001b[91mWARNING: \u001b[0mFound conflicting values for primary Corpus metadata key: 'AB'. Overwriting with secondary Corpus's metadata.\n"
      ]
     }
    ],
    "source": [
-    "corpus6 = corpus4.merge(corpus5)"
+    "corpus6 = Corpus.merge(corpus4, corpus5)"
    ]
   },
   {
@@ -355,7 +355,7 @@
     {
      "data": {
       "text/plain": [
-       "{'AB': 3, 'CD': 2, 'EF': 3}"
+       "ConvoKitMeta({'AB': 3, 'CD': 2, 'EF': 3})"
       ]
      },
      "execution_count": 16,
@@ -375,7 +375,7 @@
     {
      "data": {
       "text/plain": [
-       "Utterance({'obj_type': 'utterance', 'meta': {'fu': 'bu'}, 'vectors': [], 'speaker': Speaker({'obj_type': 'speaker', 'meta': {}, 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f1b50>, 'id': 'bob'}), 'conversation_id': '0', 'reply_to': '0', 'timestamp': None, 'text': 'my name is bob', 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f1b50>, 'id': '1'})"
+       "Utterance({'obj_type': 'utterance', 'vectors': [], 'speaker_': Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fd9c3bce700>, 'id': 'bob', 'meta': ConvoKitMeta({})}), 'owner': <convokit.model.corpus.Corpus object at 0x7fd9c3bce700>, 'id': '1', 'meta': ConvoKitMeta({'fu': 'bu'})})"
       ]
      },
      "execution_count": 17,
@@ -395,7 +395,7 @@
     {
      "data": {
       "text/plain": [
-       "Utterance({'obj_type': 'utterance', 'meta': {'in': 'the hat'}, 'vectors': [], 'speaker': Speaker({'obj_type': 'speaker', 'meta': {}, 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f1b50>, 'id': 'alice'}), 'conversation_id': '0', 'reply_to': None, 'timestamp': None, 'text': 'hello world', 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f1b50>, 'id': '0'})"
+       "Utterance({'obj_type': 'utterance', 'vectors': [], 'speaker_': Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fd9c3bce700>, 'id': 'alice', 'meta': ConvoKitMeta({})}), 'owner': <convokit.model.corpus.Corpus object at 0x7fd9c3bce700>, 'id': '0', 'meta': ConvoKitMeta({'in': 'the hat'})})"
       ]
      },
      "execution_count": 18,
@@ -422,8 +422,8 @@
     {
      "data": {
       "text/plain": [
-       "[Utterance({'obj_type': 'utterance', 'meta': {'in': 'the hat'}, 'vectors': [], 'speaker': Speaker({'obj_type': 'speaker', 'meta': {}, 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f1b50>, 'id': 'alice'}), 'conversation_id': '0', 'reply_to': None, 'timestamp': None, 'text': 'hello world', 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f1b50>, 'id': '0'}),\n",
-       " Utterance({'obj_type': 'utterance', 'meta': {'fu': 'bu'}, 'vectors': [], 'speaker': Speaker({'obj_type': 'speaker', 'meta': {}, 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f1b50>, 'id': 'bob'}), 'conversation_id': '0', 'reply_to': '0', 'timestamp': None, 'text': 'my name is bob', 'owner': <convokit.model.corpus.Corpus object at 0x7fbb118f1b50>, 'id': '1'})]"
+       "[Utterance({'obj_type': 'utterance', 'vectors': [], 'speaker_': Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fd9c3bce700>, 'id': 'alice', 'meta': ConvoKitMeta({})}), 'owner': <convokit.model.corpus.Corpus object at 0x7fd9c3bce700>, 'id': '0', 'meta': ConvoKitMeta({'in': 'the hat'})}),\n",
+       " Utterance({'obj_type': 'utterance', 'vectors': [], 'speaker_': Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x7fd9c3bce700>, 'id': 'bob', 'meta': ConvoKitMeta({})}), 'owner': <convokit.model.corpus.Corpus object at 0x7fd9c3bce700>, 'id': '1', 'meta': ConvoKitMeta({'fu': 'bu'})})]"
       ]
      },
      "execution_count": 19,
@@ -437,7 +437,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -454,9 +454,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "temp-venv",
+   "display_name": "convokit_git",
    "language": "python",
-   "name": "temp-venv"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -468,7 +468,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.9.0"
   }
  },
  "nbformat": 4,
diff --git a/examples/text-processing/text_preprocessing_demo.ipynb b/examples/text-processing/text_preprocessing_demo.ipynb
index cdcbb5b8..c910eddf 100644
--- a/examples/text-processing/text_preprocessing_demo.ipynb
+++ b/examples/text-processing/text_preprocessing_demo.ipynb
@@ -38,9 +38,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/seanzhangkx/opt/anaconda3/envs/convokit_git/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
    "source": [
     "import convokit\n",
     "from convokit import download, Speaker"
@@ -48,7 +57,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -66,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -85,7 +94,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -102,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -112,7 +121,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -121,7 +130,7 @@
        "\"Yeah, but many friends went with me, Japanese guy. So I wasn't -- I wasn't like homesick. But now sometimes I get homesick.\""
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -139,16 +148,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'is_answer': True, 'is_question': False, 'pair_idx': '1681_14'}"
+       "ConvoKitMeta({'is_answer': True, 'is_question': False, 'pair_idx': '1681_14'})"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -197,7 +206,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -220,7 +229,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -243,7 +252,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -260,7 +269,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -269,7 +278,7 @@
        "\"Yeah, but many friends went with me, Japanese guy. So I wasn't I wasn't like homesick. But now sometimes I get homesick.\""
       ]
      },
-     "execution_count": 33,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -321,7 +330,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -330,7 +339,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -339,7 +348,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -386,7 +395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -395,7 +404,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -406,17 +415,20 @@
        "  {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 5, 'dn': []},\n",
        "  {'tok': 'but', 'tag': 'CC', 'dep': 'cc', 'up': 5, 'dn': []},\n",
        "  {'tok': 'many', 'tag': 'JJ', 'dep': 'amod', 'up': 4, 'dn': []},\n",
-       "  {'tok': 'friends', 'tag': 'NNS', 'dep': 'nsubj', 'up': 5, 'dn': [3, 10]},\n",
-       "  {'tok': 'went', 'tag': 'VBD', 'dep': 'ROOT', 'dn': [0, 1, 2, 4, 6, 8, 11]},\n",
+       "  {'tok': 'friends', 'tag': 'NNS', 'dep': 'nsubj', 'up': 5, 'dn': [3]},\n",
+       "  {'tok': 'went',\n",
+       "   'tag': 'VBD',\n",
+       "   'dep': 'ROOT',\n",
+       "   'dn': [0, 1, 2, 4, 6, 8, 10, 11]},\n",
        "  {'tok': 'with', 'tag': 'IN', 'dep': 'prep', 'up': 5, 'dn': [7]},\n",
        "  {'tok': 'me', 'tag': 'PRP', 'dep': 'pobj', 'up': 6, 'dn': []},\n",
        "  {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 5, 'dn': []},\n",
        "  {'tok': 'Japanese', 'tag': 'JJ', 'dep': 'amod', 'up': 10, 'dn': []},\n",
-       "  {'tok': 'guy', 'tag': 'NN', 'dep': 'appos', 'up': 4, 'dn': [9]},\n",
+       "  {'tok': 'guy', 'tag': 'NN', 'dep': 'npadvmod', 'up': 5, 'dn': [9]},\n",
        "  {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 5, 'dn': []}]}"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -434,7 +446,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -444,7 +456,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -464,7 +476,7 @@
        "  {'tok': '.', 'tag': '.'}]}"
       ]
      },
-     "execution_count": 41,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -496,7 +508,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -505,7 +517,7 @@
        "['is_answer', 'is_question', 'pair_idx', 'clean_text', 'parsed', 'tagged']"
       ]
      },
-     "execution_count": 42,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -532,7 +544,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -555,7 +567,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -571,15 +583,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "conversations.json  index.json         info.tagged.jsonl  users.json\n",
-      "corpus.json         info.parsed.jsonl  speakers.json      utterances.jsonl\n"
+      "conversations.json  info.parsed.jsonl   \u001b[34msupreme-corpus\u001b[m\u001b[m/     \u001b[34mwiki-corpus\u001b[m\u001b[m/\n",
+      "corpus.json         info.tagged.jsonl   supreme-corpus.zip  wiki-corpus.zip\n",
+      "index.json          speakers.json       utterances.jsonl\n"
      ]
     }
    ],
@@ -589,20 +602,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'/kitchen/convokit_corpora_lf/tennis-corpus/'"
-      ]
-     },
-     "execution_count": 58,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": []
   },
   {
@@ -614,7 +616,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -623,7 +625,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -639,16 +641,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "KeysView({'is_answer': True, 'is_question': False, 'pair_idx': '1681_14'})"
+       "KeysView(ConvoKitMeta({'is_answer': True, 'is_question': False, 'pair_idx': '1681_14'}))"
       ]
      },
-     "execution_count": 62,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -666,7 +668,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -675,24 +677,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[{'rt': 5,\n",
+       "({'rt': 5,\n",
        "  'toks': [{'tok': 'Yeah', 'tag': 'UH', 'dep': 'intj', 'up': 5, 'dn': []},\n",
        "   {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 5, 'dn': []},\n",
        "   {'tok': 'but', 'tag': 'CC', 'dep': 'cc', 'up': 5, 'dn': []},\n",
        "   {'tok': 'many', 'tag': 'JJ', 'dep': 'amod', 'up': 4, 'dn': []},\n",
-       "   {'tok': 'friends', 'tag': 'NNS', 'dep': 'nsubj', 'up': 5, 'dn': [3, 10]},\n",
-       "   {'tok': 'went', 'tag': 'VBD', 'dep': 'ROOT', 'dn': [0, 1, 2, 4, 6, 8, 11]},\n",
+       "   {'tok': 'friends', 'tag': 'NNS', 'dep': 'nsubj', 'up': 5, 'dn': [3]},\n",
+       "   {'tok': 'went',\n",
+       "    'tag': 'VBD',\n",
+       "    'dep': 'ROOT',\n",
+       "    'dn': [0, 1, 2, 4, 6, 8, 10, 11]},\n",
        "   {'tok': 'with', 'tag': 'IN', 'dep': 'prep', 'up': 5, 'dn': [7]},\n",
        "   {'tok': 'me', 'tag': 'PRP', 'dep': 'pobj', 'up': 6, 'dn': []},\n",
        "   {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 5, 'dn': []},\n",
        "   {'tok': 'Japanese', 'tag': 'JJ', 'dep': 'amod', 'up': 10, 'dn': []},\n",
-       "   {'tok': 'guy', 'tag': 'NN', 'dep': 'appos', 'up': 4, 'dn': [9]},\n",
+       "   {'tok': 'guy', 'tag': 'NN', 'dep': 'npadvmod', 'up': 5, 'dn': [9]},\n",
        "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 5, 'dn': []}]},\n",
        " {'rt': 2,\n",
        "  'toks': [{'tok': 'So', 'tag': 'RB', 'dep': 'advmod', 'up': 2, 'dn': []},\n",
@@ -700,10 +705,10 @@
        "   {'tok': 'was', 'tag': 'VBD', 'dep': 'ROOT', 'dn': [0, 1, 3, 5, 9]},\n",
        "   {'tok': \"n't\", 'tag': 'RB', 'dep': 'neg', 'up': 2, 'dn': []},\n",
        "   {'tok': 'I', 'tag': 'PRP', 'dep': 'nsubj', 'up': 5, 'dn': []},\n",
-       "   {'tok': 'was', 'tag': 'VBD', 'dep': 'ccomp', 'up': 2, 'dn': [4, 6, 8]},\n",
+       "   {'tok': 'was', 'tag': 'VBD', 'dep': 'ccomp', 'up': 2, 'dn': [4, 6, 7]},\n",
        "   {'tok': \"n't\", 'tag': 'RB', 'dep': 'neg', 'up': 5, 'dn': []},\n",
-       "   {'tok': 'like', 'tag': 'UH', 'dep': 'intj', 'up': 8, 'dn': []},\n",
-       "   {'tok': 'homesick', 'tag': 'JJ', 'dep': 'acomp', 'up': 5, 'dn': [7]},\n",
+       "   {'tok': 'like', 'tag': 'IN', 'dep': 'prep', 'up': 5, 'dn': [8]},\n",
+       "   {'tok': 'homesick', 'tag': 'NN', 'dep': 'pobj', 'up': 7, 'dn': []},\n",
        "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 2, 'dn': []}]},\n",
        " {'rt': 4,\n",
        "  'toks': [{'tok': 'But', 'tag': 'CC', 'dep': 'cc', 'up': 4, 'dn': []},\n",
@@ -712,10 +717,10 @@
        "   {'tok': 'I', 'tag': 'PRP', 'dep': 'nsubj', 'up': 4, 'dn': []},\n",
        "   {'tok': 'get', 'tag': 'VBP', 'dep': 'ROOT', 'dn': [0, 1, 2, 3, 5, 6]},\n",
        "   {'tok': 'homesick', 'tag': 'JJ', 'dep': 'acomp', 'up': 4, 'dn': []},\n",
-       "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 4, 'dn': []}]}]"
+       "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 4, 'dn': []}]})"
       ]
      },
-     "execution_count": 68,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -753,7 +758,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -762,16 +767,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Utterance({'obj_type': 'utterance', 'meta': {'clean_text': 'I played a tennis match.'}, 'vectors': [], 'speaker': Speaker({'obj_type': 'speaker', 'meta': {}, 'vectors': [], 'owner': None, 'id': 'speaker'}), 'conversation_id': None, 'reply_to': None, 'timestamp': None, 'text': 'I played -- a tennis match.', 'owner': None, 'id': None})"
+       "Utterance({'obj_type': 'utterance', 'vectors': [], 'speaker_': Speaker({'obj_type': 'speaker', 'vectors': [], 'owner': None, 'id': 'speaker', 'temp_storage': {}, 'meta': {}}), 'owner': None, 'id': None, 'temp_storage': {'speaker_id': 'speaker', 'conversation_id': None, 'reply_to': None, 'timestamp': None, 'text': 'I played -- a tennis match.'}, 'meta': {'clean_text': 'I played a tennis match.'}})"
       ]
      },
-     "execution_count": 70,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -782,16 +787,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
-    "adhoc_utt = prep.transform_utterance(adhoc_utt)"
+    "adhoc_utt = prep.transform_utterance(test_str)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -800,7 +805,7 @@
        "'I played a tennis match.'"
       ]
      },
-     "execution_count": 74,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -832,7 +837,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -851,7 +856,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -862,7 +867,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -882,24 +887,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[{'rt': 5,\n",
+       "({'rt': 5,\n",
        "  'toks': [{'tok': 'Yeah', 'tag': 'UH', 'dep': 'intj', 'up': 5, 'dn': []},\n",
        "   {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 5, 'dn': []},\n",
        "   {'tok': 'but', 'tag': 'CC', 'dep': 'cc', 'up': 5, 'dn': []},\n",
        "   {'tok': 'many', 'tag': 'JJ', 'dep': 'amod', 'up': 4, 'dn': []},\n",
-       "   {'tok': 'friends', 'tag': 'NNS', 'dep': 'nsubj', 'up': 5, 'dn': [3, 10]},\n",
-       "   {'tok': 'went', 'tag': 'VBD', 'dep': 'ROOT', 'dn': [0, 1, 2, 4, 6, 8, 11]},\n",
+       "   {'tok': 'friends', 'tag': 'NNS', 'dep': 'nsubj', 'up': 5, 'dn': [3]},\n",
+       "   {'tok': 'went',\n",
+       "    'tag': 'VBD',\n",
+       "    'dep': 'ROOT',\n",
+       "    'dn': [0, 1, 2, 4, 6, 8, 10, 11]},\n",
        "   {'tok': 'with', 'tag': 'IN', 'dep': 'prep', 'up': 5, 'dn': [7]},\n",
        "   {'tok': 'me', 'tag': 'PRP', 'dep': 'pobj', 'up': 6, 'dn': []},\n",
        "   {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 5, 'dn': []},\n",
        "   {'tok': 'Japanese', 'tag': 'JJ', 'dep': 'amod', 'up': 10, 'dn': []},\n",
-       "   {'tok': 'guy', 'tag': 'NN', 'dep': 'appos', 'up': 4, 'dn': [9]},\n",
+       "   {'tok': 'guy', 'tag': 'NN', 'dep': 'npadvmod', 'up': 5, 'dn': [9]},\n",
        "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 5, 'dn': []}]},\n",
        " {'rt': 2,\n",
        "  'toks': [{'tok': 'So', 'tag': 'RB', 'dep': 'advmod', 'up': 2, 'dn': []},\n",
@@ -907,10 +915,10 @@
        "   {'tok': 'was', 'tag': 'VBD', 'dep': 'ROOT', 'dn': [0, 1, 3, 5, 9]},\n",
        "   {'tok': \"n't\", 'tag': 'RB', 'dep': 'neg', 'up': 2, 'dn': []},\n",
        "   {'tok': 'I', 'tag': 'PRP', 'dep': 'nsubj', 'up': 5, 'dn': []},\n",
-       "   {'tok': 'was', 'tag': 'VBD', 'dep': 'ccomp', 'up': 2, 'dn': [4, 6, 8]},\n",
+       "   {'tok': 'was', 'tag': 'VBD', 'dep': 'ccomp', 'up': 2, 'dn': [4, 6, 7]},\n",
        "   {'tok': \"n't\", 'tag': 'RB', 'dep': 'neg', 'up': 5, 'dn': []},\n",
-       "   {'tok': 'like', 'tag': 'UH', 'dep': 'intj', 'up': 8, 'dn': []},\n",
-       "   {'tok': 'homesick', 'tag': 'JJ', 'dep': 'acomp', 'up': 5, 'dn': [7]},\n",
+       "   {'tok': 'like', 'tag': 'IN', 'dep': 'prep', 'up': 5, 'dn': [8]},\n",
+       "   {'tok': 'homesick', 'tag': 'NN', 'dep': 'pobj', 'up': 7, 'dn': []},\n",
        "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 2, 'dn': []}]},\n",
        " {'rt': 4,\n",
        "  'toks': [{'tok': 'But', 'tag': 'CC', 'dep': 'cc', 'up': 4, 'dn': []},\n",
@@ -919,10 +927,10 @@
        "   {'tok': 'I', 'tag': 'PRP', 'dep': 'nsubj', 'up': 4, 'dn': []},\n",
        "   {'tok': 'get', 'tag': 'VBP', 'dep': 'ROOT', 'dn': [0, 1, 2, 3, 5, 6]},\n",
        "   {'tok': 'homesick', 'tag': 'JJ', 'dep': 'acomp', 'up': 4, 'dn': []},\n",
-       "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 4, 'dn': []}]}]"
+       "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 4, 'dn': []}]})"
       ]
      },
-     "execution_count": 78,
+     "execution_count": 38,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -940,7 +948,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -949,7 +957,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -964,7 +972,7 @@
        "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 1, 'dn': []}]}]"
       ]
      },
-     "execution_count": 80,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -998,7 +1006,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1008,7 +1016,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
@@ -1017,7 +1025,7 @@
        "23"
       ]
      },
-     "execution_count": 83,
+     "execution_count": 42,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1035,7 +1043,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1052,7 +1060,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
@@ -1061,7 +1069,7 @@
        "22"
       ]
      },
-     "execution_count": 86,
+     "execution_count": 44,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1079,7 +1087,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1089,7 +1097,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
@@ -1098,7 +1106,7 @@
        "120"
       ]
      },
-     "execution_count": 88,
+     "execution_count": 46,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1133,7 +1141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1144,7 +1152,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
@@ -1153,7 +1161,7 @@
        "5.454545454545454"
       ]
      },
-     "execution_count": 90,
+     "execution_count": 48,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1164,7 +1172,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [
     {
@@ -1173,7 +1181,7 @@
        "0.18333333333333332"
       ]
      },
-     "execution_count": 91,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1205,7 +1213,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1215,7 +1223,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1224,7 +1232,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 94,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [
     {
@@ -1251,7 +1259,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 53,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1267,7 +1275,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [
     {
@@ -1276,7 +1284,7 @@
        "'How hard was it for you when, 13 years, left your parents, left Japan to go to the States. Was it a big step for you?'"
       ]
      },
-     "execution_count": 96,
+     "execution_count": 54,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1289,7 +1297,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 55,
    "metadata": {
     "scrolled": true
    },
@@ -1297,30 +1305,30 @@
     {
      "data": {
       "text/plain": [
-       "[{'rt': 11,\n",
+       "({'rt': 15,\n",
        "  'toks': [{'tok': 'How', 'tag': 'WRB', 'dep': 'advmod', 'up': 1, 'dn': []},\n",
        "   {'tok': 'hard', 'tag': 'RB', 'dep': 'acomp', 'up': 2, 'dn': [0]},\n",
-       "   {'tok': 'was', 'tag': 'VBD', 'dep': 'advcl', 'up': 11, 'dn': [1, 3, 4, 9]},\n",
+       "   {'tok': 'was', 'tag': 'VBD', 'dep': 'advcl', 'up': 15, 'dn': [1, 3, 4, 11]},\n",
        "   {'tok': 'it', 'tag': 'PRP', 'dep': 'nsubj', 'up': 2, 'dn': []},\n",
        "   {'tok': 'for', 'tag': 'IN', 'dep': 'prep', 'up': 2, 'dn': [5]},\n",
        "   {'tok': 'you', 'tag': 'PRP', 'dep': 'pobj', 'up': 4, 'dn': []},\n",
-       "   {'tok': 'when', 'tag': 'WRB', 'dep': 'advmod', 'up': 9, 'dn': [7]},\n",
-       "   {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 6, 'dn': []},\n",
-       "   {'tok': '13', 'tag': 'CD', 'dep': 'nummod', 'up': 9, 'dn': []},\n",
-       "   {'tok': 'years', 'tag': 'NNS', 'dep': 'npadvmod', 'up': 2, 'dn': [6, 8]},\n",
+       "   {'tok': 'when', 'tag': 'WRB', 'dep': 'advmod', 'up': 11, 'dn': []},\n",
        "   {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 11, 'dn': []},\n",
-       "   {'tok': 'left', 'tag': 'VBD', 'dep': 'ROOT', 'dn': [2, 10, 13, 14, 15, 22]},\n",
+       "   {'tok': '13', 'tag': 'CD', 'dep': 'nummod', 'up': 9, 'dn': []},\n",
+       "   {'tok': 'years', 'tag': 'NNS', 'dep': 'nsubj', 'up': 11, 'dn': [8, 10]},\n",
+       "   {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 9, 'dn': []},\n",
+       "   {'tok': 'left', 'tag': 'VBD', 'dep': 'advcl', 'up': 2, 'dn': [6, 7, 9, 13]},\n",
        "   {'tok': 'your', 'tag': 'PRP$', 'dep': 'poss', 'up': 13, 'dn': []},\n",
        "   {'tok': 'parents', 'tag': 'NNS', 'dep': 'dobj', 'up': 11, 'dn': [12]},\n",
-       "   {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 11, 'dn': []},\n",
-       "   {'tok': 'left', 'tag': 'VBD', 'dep': 'conj', 'up': 11, 'dn': [16, 18]},\n",
+       "   {'tok': ',', 'tag': ',', 'dep': 'punct', 'up': 15, 'dn': []},\n",
+       "   {'tok': 'left', 'tag': 'VBD', 'dep': 'ROOT', 'dn': [2, 14, 16, 18, 22]},\n",
        "   {'tok': 'Japan', 'tag': 'NNP', 'dep': 'dobj', 'up': 15, 'dn': []},\n",
        "   {'tok': 'to', 'tag': 'TO', 'dep': 'aux', 'up': 18, 'dn': []},\n",
        "   {'tok': 'go', 'tag': 'VB', 'dep': 'xcomp', 'up': 15, 'dn': [17, 19]},\n",
        "   {'tok': 'to', 'tag': 'IN', 'dep': 'prep', 'up': 18, 'dn': [21]},\n",
        "   {'tok': 'the', 'tag': 'DT', 'dep': 'det', 'up': 21, 'dn': []},\n",
-       "   {'tok': 'States', 'tag': 'NNP', 'dep': 'pobj', 'up': 19, 'dn': [20]},\n",
-       "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 11, 'dn': []}]},\n",
+       "   {'tok': 'States', 'tag': 'NNPS', 'dep': 'pobj', 'up': 19, 'dn': [20]},\n",
+       "   {'tok': '.', 'tag': '.', 'dep': 'punct', 'up': 15, 'dn': []}]},\n",
        " {'rt': 0,\n",
        "  'toks': [{'tok': 'Was', 'tag': 'VBD', 'dep': 'ROOT', 'dn': [1, 4, 7]},\n",
        "   {'tok': 'it', 'tag': 'PRP', 'dep': 'nsubj', 'up': 0, 'dn': []},\n",
@@ -1329,10 +1337,10 @@
        "   {'tok': 'step', 'tag': 'NN', 'dep': 'attr', 'up': 0, 'dn': [2, 3, 5]},\n",
        "   {'tok': 'for', 'tag': 'IN', 'dep': 'prep', 'up': 4, 'dn': [6]},\n",
        "   {'tok': 'you', 'tag': 'PRP', 'dep': 'pobj', 'up': 5, 'dn': []},\n",
-       "   {'tok': '?', 'tag': '.', 'dep': 'punct', 'up': 0, 'dn': []}]}]"
+       "   {'tok': '?', 'tag': '.', 'dep': 'punct', 'up': 0, 'dn': []}]})"
       ]
      },
-     "execution_count": 97,
+     "execution_count": 55,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1372,7 +1380,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.9.0"
   }
  },
  "nbformat": 4,