{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":64,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":64,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"b1498563ec9f","filters":{"venue":"Social Network Analysis and Mining"}},"results":[{"id":"W4319983294","doi":"10.1007/s13278-023-01028-5","title":"Fake news, disinformation and misinformation in social media: a review","year":2023,"lang":"en","type":"review","venue":"Social Network Analysis and Mining","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":677,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Disinformation; Misinformation; Computer science; Fake news; Social media; Internet privacy; Data science; News media; Dissemination; Identification (biology); Computer security; World Wide Web; Advertising; Business; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.09155576014776821,"gpt":0.3966385923297672,"spread":0.305082832181999,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002673825,0.0003027224,0.001777205,0.0005900241,0.001275838,0.0003406655,0.0001649311,0.000434467,0.00007037815],"category_scores_gemma":[0.0005150785,0.0002760243,0.0004451162,0.004502103,0.0001586714,0.0007537088,0.00008832775,0.0002999922,0.00002547845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001451601,"about_ca_system_score_gemma":0.0002659338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002126712,"about_ca_topic_score_gemma":0.004927561,"domain_scores_codex":[0.997062,0.0003862015,0.001272543,0.000210089,0.0005488403,0.0005203539],"domain_scores_gemma":[0.9982882,0.0004030952,0.000978713,0.0000921856,0.00008342847,0.0001543456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001227488,0.00000344805,0.00001546273,0.003855198,0.0002369189,7.489487e-7,0.04558339,0.00000208024,2.434037e-10,0.00186489,0.008857601,0.939579],"study_design_scores_gemma":[0.0001407362,0.000004933676,0.000283042,0.006323685,0.002826276,7.254307e-7,0.01408873,0.00009785165,5.74606e-10,0.0001583448,0.9757051,0.0003705403],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000406441,0.9896912,0.00008217893,0.0003988823,0.0001571979,0.0005365517,0.00002724075,0.0000800846,0.008986008],"genre_scores_gemma":[0.00006808956,0.9976779,0.00006728991,0.0003042937,0.001033479,0.00001702514,0.0005892881,0.00001711676,0.0002255109],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9668475,"threshold_uncertainty_score":0.9999692,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2796430037","doi":"10.1007/s13278-018-0505-2","title":"Emotion detection from text and speech: a survey","year":2018,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":260,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Popularity; Field (mathematics); Task (project management); Variety (cybernetics); Emotion classification; Sentence; Natural language processing; Emotion detection; Domain (mathematical analysis); Artificial intelligence; Focus (optics); Gesture; Feature (linguistics); Affective computing; Social media; Emotion recognition; Psychology; Linguistics; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.0385336209295106,"gpt":0.3111448165432063,"spread":0.2726111956136957,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004841835,0.00008844955,0.0001986096,0.0001026949,0.0003893392,0.00004785899,0.00002487948,0.0001351692,0.0005552908],"category_scores_gemma":[0.00002320244,0.00008907247,0.00007004417,0.0005964948,0.00009003962,0.00004485754,0.00002078592,0.00007547955,0.00002786148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000950582,"about_ca_system_score_gemma":0.000003909352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001430911,"about_ca_topic_score_gemma":0.01174765,"domain_scores_codex":[0.9990489,0.0002769174,0.0001650495,0.000264695,0.00007331985,0.0001711183],"domain_scores_gemma":[0.9996151,0.00009150839,0.0001053245,0.00006531815,0.00007161679,0.00005116186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00008310092,0.00003401352,0.1670862,0.000001767372,0.001077336,0.000002029348,0.006307488,0.000002061868,0.0001173181,0.00009640714,0.001452739,0.8237395],"study_design_scores_gemma":[0.0003320527,0.00006791235,0.995214,0.000006432896,0.0005855717,0.000001388967,0.001545298,0.0008555776,0.00002152065,0.0004889939,0.0007592485,0.0001220309],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846511,0.0001683722,0.01028122,0.00005105656,0.0003966368,0.00004892983,0.00001110196,0.00003369372,0.004357857],"genre_scores_gemma":[0.9973234,0.00003484781,0.0003519124,0.0001586541,0.001561063,0.000003299681,0.0001040382,0.00000878002,0.00045399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8281278,"threshold_uncertainty_score":0.6555464,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2070199170","doi":"10.1007/s13278-012-0062-z","title":"On minimizing budget and time in influence propagation over social networks","year":2012,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":147,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Viral marketing; Maximization; Task (project management); Set (abstract data type); Computer science; Budget constraint; Context (archaeology); Mathematical optimization; Selection (genetic algorithm); Mathematics; Artificial intelligence; Economics; Social media","retraction":null,"screen_n_in":null,"score":{"opus":0.006771410045472699,"gpt":0.2553418218687794,"spread":0.2485704118233067,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006434823,0.0002221327,0.000527184,0.0001993645,0.0005003763,0.00007938594,0.00008318359,0.00009655108,0.000108902],"category_scores_gemma":[0.000006683209,0.0002258317,0.0001830451,0.001299333,0.00008907561,0.0002088162,0.000105551,0.0002168442,0.000001916662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003379995,"about_ca_system_score_gemma":0.00001145229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000142032,"about_ca_topic_score_gemma":0.00005043348,"domain_scores_codex":[0.9984516,0.0001652901,0.0003677245,0.0003089733,0.0001733022,0.0005331194],"domain_scores_gemma":[0.9993834,0.0001621676,0.0002339034,0.00009867712,0.0000375652,0.00008432597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003613543,0.00008596214,0.9315463,0.000005180945,0.0008088833,7.999452e-7,0.002597302,0.006851132,0.00003819225,0.01305528,0.002111763,0.04286304],"study_design_scores_gemma":[0.000566503,0.00004277458,0.8463497,0.00005312379,0.00149645,2.742245e-7,0.0005748432,0.1453994,0.00001025592,0.004110207,0.0007248722,0.0006716724],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906415,0.0002782454,0.006866259,0.00006547903,0.00002499966,0.0001256885,0.000002965576,0.00003965725,0.001955171],"genre_scores_gemma":[0.9975328,0.00001339772,0.0006806422,0.0001155698,0.001475282,0.00002670427,0.00005992164,0.0000187587,0.00007689439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1385482,"threshold_uncertainty_score":0.9209148,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1967097654","doi":"10.1007/s13278-014-0193-5","title":"Predicting political preference of Twitter users","year":2014,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":99,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Preference; Computer science; Variety (cybernetics); Context (archaeology); Politics; Sentiment analysis; Artificial intelligence; Work (physics); Natural language processing; Information retrieval; Political science; Law; Mathematics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.02924801817375477,"gpt":0.2670297265927906,"spread":0.2377817084190358,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006280035,0.0001152886,0.0003969531,0.0001631127,0.0002554681,0.0001051736,0.0002647441,0.00006483711,0.00001929486],"category_scores_gemma":[0.0000360949,0.0001054346,0.0002226936,0.001188014,0.00006688297,0.0001400527,0.0001787556,0.00008028536,0.000001282846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001048295,"about_ca_system_score_gemma":0.00001432501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005618557,"about_ca_topic_score_gemma":0.00002905493,"domain_scores_codex":[0.9985821,0.0001277929,0.0003465275,0.0003212652,0.0002518663,0.0003704341],"domain_scores_gemma":[0.9992713,0.0001823224,0.000196206,0.0001873533,0.00006743297,0.00009534037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000034499,0.00001971739,0.8759153,0.000008956733,0.0008325224,5.744729e-7,0.002332422,0.0007575373,0.00003677394,0.1069668,0.0002512371,0.01287467],"study_design_scores_gemma":[0.000369724,0.00007669102,0.2579931,0.00004305788,0.001175032,7.637659e-7,0.001189678,0.7345226,0.00009453687,0.003461838,0.0007289563,0.0003439996],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6911589,0.0000813361,0.3046686,0.0003479381,0.00009542632,0.00003229985,5.080854e-7,0.00004010172,0.003574895],"genre_scores_gemma":[0.9839324,0.000006780201,0.01539265,0.0002124903,0.0003603698,0.000002327096,0.000005162406,0.000004759169,0.00008303498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7337651,"threshold_uncertainty_score":0.4299498,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4220686914","doi":"10.1007/s13278-022-00869-w","title":"DeeProBot: a hybrid deep neural network model for social bot detection based on user profile data","year":2022,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":83,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Zayed University","keywords":"Computer science; Artificial neural network; Artificial intelligence; Social network (sociolinguistics); Data mining; Machine learning; Social media; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.03954773012374535,"gpt":0.2695036051973896,"spread":0.2299558750736443,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001153156,0.0001800878,0.0003330652,0.000132939,0.003314662,0.0002602656,0.0005977403,0.00006148577,0.00001456001],"category_scores_gemma":[0.00002503079,0.000198508,0.0002296239,0.001483939,0.00003258643,0.0002687861,0.0004347431,0.000245622,5.665423e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007284704,"about_ca_system_score_gemma":0.00004365522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003419378,"about_ca_topic_score_gemma":0.0003293702,"domain_scores_codex":[0.9979731,0.000221349,0.0002771247,0.0007059688,0.0003468454,0.0004756071],"domain_scores_gemma":[0.9991347,0.0001568686,0.0002310874,0.0003616155,0.00005323361,0.00006253407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000867972,0.00003117256,0.0007094766,0.000005499473,0.0001967623,0.000001931093,0.0007125624,0.9033332,0.00001003999,0.0003717589,0.00280731,0.09173353],"study_design_scores_gemma":[0.0003366045,0.0001049824,0.0009938536,0.000002042621,0.0003792373,0.000001065944,0.00006604535,0.9961125,0.000005113096,0.001032864,0.0007425888,0.000223141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02065276,0.00009896008,0.977894,0.0003984915,0.0004728364,0.000233502,0.00002574868,0.0001253485,0.00009831921],"genre_scores_gemma":[0.9770885,0.000002027097,0.02016204,0.0007111428,0.001634936,0.0001365259,0.0001701957,0.00001994944,0.00007475408],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.957732,"threshold_uncertainty_score":0.9979829,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2039552732","doi":"10.1007/s13278-014-0154-z","title":"Interactive discovery of influential friends from social networks","year":2014,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":66,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Interdependence; Centrality; Friendship; Computer science; Social network (sociolinguistics); Social network analysis; Data science; World Wide Web; Social media; Sociology; Social science","retraction":null,"screen_n_in":null,"score":{"opus":0.005928328827660596,"gpt":0.2549476657562682,"spread":0.2490193369286076,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003509526,0.0002431844,0.0008506002,0.0001494302,0.0004818217,0.0001387598,0.0001913824,0.00009535043,0.0001999241],"category_scores_gemma":[0.000004860328,0.0002455983,0.0006639747,0.001175199,0.0001559322,0.0002149128,0.0002135736,0.0002212509,7.935339e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001863179,"about_ca_system_score_gemma":0.00001604407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000993061,"about_ca_topic_score_gemma":0.0002365628,"domain_scores_codex":[0.9982643,0.0002241251,0.000525076,0.0004008563,0.0002092534,0.0003763947],"domain_scores_gemma":[0.9989166,0.0002509344,0.0005164593,0.0001682474,0.0000922702,0.00005545911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001458998,0.0001672613,0.7369836,0.000006346903,0.01478831,9.618412e-7,0.005012921,0.01063393,0.0001245072,0.0357261,0.003710285,0.1926999],"study_design_scores_gemma":[0.001862596,0.0001639387,0.527719,0.0001047286,0.02209896,1.870688e-7,0.005734618,0.3911647,0.0002440637,0.0429306,0.006130503,0.001846151],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6498019,0.00007670475,0.3461847,0.00003862894,0.00007925344,0.00005580449,0.00002172919,0.00003519465,0.003706055],"genre_scores_gemma":[0.9942479,0.000005359065,0.001412686,0.00005317378,0.003915504,0.00001361219,0.0002549388,0.00002117341,0.00007570376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3805307,"threshold_uncertainty_score":0.9999996,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2075793500","doi":"10.1007/s13278-012-0084-6","title":"Why Waldo befriended the dummy? k-Anonymization of social networks with pseudo-nodes","year":2012,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Anonymity; Adversary; Computer science; Privacy protection; Social network (sociolinguistics); Graph; Identity (music); Representation (politics); Degree (music); Theoretical computer science; k-anonymity; Computer security; Focus (optics); Social media; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.01549301093132363,"gpt":0.2491565590740119,"spread":0.2336635481426882,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007901167,0.0001645775,0.0003961384,0.0001052835,0.0008055861,0.0001341653,0.003605741,0.0001507272,0.00001217122],"category_scores_gemma":[0.0004397978,0.0001166908,0.0001318419,0.002465939,0.0002568634,0.0004428226,0.006934091,0.0001833382,3.890019e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002508092,"about_ca_system_score_gemma":0.00002095248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008807828,"about_ca_topic_score_gemma":0.0001954865,"domain_scores_codex":[0.9984769,0.0001625828,0.0002904772,0.0002914834,0.0002863853,0.0004921997],"domain_scores_gemma":[0.9982212,0.0002039888,0.0003410766,0.001106544,0.00008367703,0.00004349339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001218715,0.0003242638,0.4129212,0.000143257,0.008695289,0.000008014275,0.02282764,0.01363291,0.00006117077,0.1171362,0.3560504,0.06807765],"study_design_scores_gemma":[0.0007197452,0.0001027312,0.08005624,0.00007759631,0.003227356,0.000005777602,0.002171925,0.8964397,0.00006987715,0.01352014,0.00274536,0.0008635059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05810137,0.0005846499,0.9329045,0.007116812,0.0001538034,0.000138106,0.00000565577,0.0001776322,0.0008174581],"genre_scores_gemma":[0.9398893,0.00004052567,0.05918954,0.0003644084,0.0004434476,0.00001220682,0.00002849174,0.00001103344,0.00002112077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8828068,"threshold_uncertainty_score":0.8642848,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2017533400","doi":"10.1007/s13278-013-0122-z","title":"Trust prediction from user-item ratings","year":2013,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Access Control and Trust","field":"Social Sciences","cited_by":44,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Variety (cybernetics); Focus (optics); Set (abstract data type); Product (mathematics); Social network (sociolinguistics); Machine learning; Data mining; Data science; Artificial intelligence; Information retrieval; Social media; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.0104398940578091,"gpt":0.2528056440147893,"spread":0.2423657499569802,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003666669,0.00009846211,0.0002813908,0.00006033286,0.001578908,0.0003171041,0.000111205,0.0001274491,0.0007189693],"category_scores_gemma":[0.00006672856,0.00009262966,0.0001547844,0.0008305229,0.0001366064,0.0003237682,0.00003817437,0.00009464251,0.0000130795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002674785,"about_ca_system_score_gemma":0.00002985023,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01779826,"about_ca_topic_score_gemma":0.005292658,"domain_scores_codex":[0.9988396,0.0001514189,0.0002243721,0.0002337951,0.0002358378,0.0003150098],"domain_scores_gemma":[0.9994522,0.0001502681,0.0001475074,0.00006490051,0.00008239027,0.0001027363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006134499,0.00001415386,0.8823279,0.000001301519,0.0007278927,0.000001000314,0.01420874,0.00009665395,0.00001253991,0.003092656,0.004490594,0.09502048],"study_design_scores_gemma":[0.0003448221,0.00001562608,0.949859,0.00001033694,0.001223574,3.922945e-8,0.01740489,0.009681419,0.000001205894,0.002683358,0.0185547,0.000221018],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818881,0.0003560292,0.001641184,0.0008698764,0.0001827574,0.0001238779,0.000009536911,0.00008026038,0.01484843],"genre_scores_gemma":[0.9949909,0.00008692034,0.0006147866,0.000225347,0.002769272,0.00002403216,0.00003220494,0.00000723403,0.001249336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09479946,"threshold_uncertainty_score":0.9997209,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2333444811","doi":"10.1007/s13278-016-0324-2","title":"Discover millions of fake followers in Weibo","year":2016,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Task (project management); Social media; Cluster (spacecraft); World Wide Web; Information retrieval; Data mining; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.008665795947851405,"gpt":0.2309510945316115,"spread":0.2222852985837601,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002733096,0.00005699335,0.0001808047,0.000127711,0.0001076505,0.00003079755,0.000122476,0.00004416407,0.000007481543],"category_scores_gemma":[0.00001587225,0.0000415756,0.000119071,0.001235969,0.00003395322,0.0001527691,0.00005845372,0.00003226056,7.024595e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001369926,"about_ca_system_score_gemma":0.00001388858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001205234,"about_ca_topic_score_gemma":0.0008244003,"domain_scores_codex":[0.9993743,0.00004793688,0.0001539157,0.0001696392,0.0001036294,0.0001505573],"domain_scores_gemma":[0.9996881,0.00009069368,0.00007955683,0.00009791448,0.00001685907,0.00002686979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001764062,0.00004141903,0.5491314,0.000006125204,0.0006446077,0.000006216353,0.007271236,0.0009356649,0.0006445138,0.01475435,0.001122007,0.4254248],"study_design_scores_gemma":[0.001448964,0.0001792012,0.9510734,0.0001434214,0.0007223532,0.000001389546,0.0008539718,0.02618549,0.0002407451,0.0126171,0.005888594,0.0006453631],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7712739,0.0001990803,0.2271409,0.000442116,0.0001809152,0.0000284601,0.000001461536,0.0000179276,0.0007152522],"genre_scores_gemma":[0.9975914,0.00003967122,0.002072622,0.00003943166,0.0001286519,0.000002188144,7.167602e-7,0.000002474826,0.0001228151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4247795,"threshold_uncertainty_score":0.1695404,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2034464123","doi":"10.1007/s13278-010-0015-3","title":"Promoting where, when and what? An analysis of web logs by integrating data mining and social network techniques to guide ecommerce business promotions","year":2010,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":31,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Data science; Social network analysis; Web mining; Computer science; World Wide Web; Social commerce; Social network (sociolinguistics); Data mining; Knowledge management; Social media; Business; Web service","retraction":null,"screen_n_in":null,"score":{"opus":0.0180227438065476,"gpt":0.303615564202031,"spread":0.2855928203954834,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.002170091,0.0004579326,0.001470081,0.000501644,0.0013432,0.0008012528,0.0005253257,0.0002092805,0.0001017136],"category_scores_gemma":[0.00003422042,0.0004655622,0.000267956,0.003906851,0.0002572554,0.0009043382,0.0008487439,0.0003936197,1.388053e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002429314,"about_ca_system_score_gemma":0.00006394904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001353534,"about_ca_topic_score_gemma":0.01223619,"domain_scores_codex":[0.9966536,0.0003224668,0.001004612,0.001043299,0.0002999177,0.0006760815],"domain_scores_gemma":[0.9978914,0.000265917,0.0007408567,0.0005767656,0.0003309897,0.0001940412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001825221,0.0001460768,0.4482704,0.00003043988,0.007288469,0.000001308069,0.01141631,0.0001742747,0.001159723,0.001110106,0.008102589,0.5222821],"study_design_scores_gemma":[0.0009736831,0.0003389901,0.1096113,0.0005964233,0.06038769,0.00000360245,0.04150583,0.7532601,0.0001449995,0.003666379,0.02609606,0.003414981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9589019,0.000509823,0.03864149,0.0008889384,0.00005996528,0.0003687992,0.0001110721,0.0001433292,0.000374706],"genre_scores_gemma":[0.9306386,0.00007772374,0.06652385,0.0001169439,0.001358801,0.0000494437,0.001124692,0.00004737014,0.00006265197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7530858,"threshold_uncertainty_score":0.9999569,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2026619283","doi":"10.1007/s13278-014-0242-0","title":"Verification of lack of emergent behavior in extending a social network of agents","year":2015,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Computer science; Scalability; Deadlock; Notation; System requirements specification; Requirements analysis; Software engineering; System requirements; Simplicity; Software; Systems engineering; Distributed computing; Programming language; Database; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1448936097752953,"gpt":0.3776003162795531,"spread":0.2327067065042579,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001040119,0.00008733734,0.0004477295,0.0001041134,0.00005657128,0.000006944141,0.000202794,0.00006948622,0.000001765454],"category_scores_gemma":[0.0001208836,0.00009371973,0.0001251384,0.001585411,0.00006096155,0.00009328019,0.0001238392,0.00006442186,7.197502e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002939196,"about_ca_system_score_gemma":0.00002806183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003222599,"about_ca_topic_score_gemma":0.00002509096,"domain_scores_codex":[0.9988524,0.0001548803,0.0004229688,0.0001827608,0.0001922033,0.0001948178],"domain_scores_gemma":[0.99925,0.0001328913,0.0003613961,0.000122247,0.0001021826,0.0000312808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00004029158,0.00009871891,0.2614171,0.00005069523,0.0004756675,0.000004065936,0.01683224,0.6069492,0.0004552023,0.008611741,0.00035816,0.1047069],"study_design_scores_gemma":[0.0007400888,0.0001478052,0.9364031,0.00007205273,0.00079935,5.434937e-7,0.001993101,0.05141501,0.0003278139,0.007541569,0.0001495379,0.0004100331],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4095753,0.0003241363,0.5898852,0.00001434359,0.0001180928,0.00004303666,0.000001062564,0.00001481537,0.00002408569],"genre_scores_gemma":[0.8242881,0.00003958031,0.1755307,0.0000045347,0.0001142439,0.00000646871,0.000003743942,0.000004709327,0.000008001188],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.674986,"threshold_uncertainty_score":0.3821779,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2190512236","doi":"10.1007/s13278-015-0303-z","title":"Analysis of collaborative learning in social network sites used in education","year":2015,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Impact of Technology on Adolescents","field":"Social Sciences","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Mainstream; Computer science; Collaborative learning; Field (mathematics); The Internet; Soar; World Wide Web; Knowledge management; Psychology; Artificial intelligence; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.02423514735239957,"gpt":0.3410443341967647,"spread":0.3168091868443652,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002269547,0.0001358936,0.0007559262,0.0007719398,0.0006199258,0.00007124781,0.0001641071,0.0002813601,0.00002277215],"category_scores_gemma":[0.0003223545,0.0001561423,0.0001826507,0.01552613,0.0003041671,0.0001529135,0.0000633544,0.0002511751,7.58381e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002211283,"about_ca_system_score_gemma":0.0004227368,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002255469,"about_ca_topic_score_gemma":0.07014877,"domain_scores_codex":[0.9977338,0.0007273059,0.0004345288,0.0002730674,0.0003483557,0.0004829408],"domain_scores_gemma":[0.9991041,0.0001423702,0.0004084909,0.00007039229,0.0001911376,0.0000835256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002596949,0.00006212189,0.9370623,0.000002168583,0.0008152106,0.000001188671,0.04259216,0.009122932,0.000002870515,0.001068564,0.0008202391,0.008424252],"study_design_scores_gemma":[0.0004512213,0.00003015851,0.8760804,0.00002478914,0.002053975,2.47579e-8,0.1157474,0.003422987,0.000001305173,0.001087165,0.0008677654,0.0002328282],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955404,0.0006187985,0.0000995822,0.000617782,0.00008567362,0.000124066,0.00000224311,0.00003647828,0.002874987],"genre_scores_gemma":[0.9985862,0.00008376698,0.0004830578,0.00008031579,0.0004701856,0.00000973507,0.00004117737,0.000008475649,0.0002371048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07315524,"threshold_uncertainty_score":0.9468186,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4288715199","doi":"10.1007/s13278-022-00921-9","title":"Applications of machine learning for COVID-19 misinformation: a systematic review","year":2022,"lang":"en","type":"review","venue":"Social Network Analysis and Mining","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Misinformation; Computer science; Coronavirus disease 2019 (COVID-19); Artificial intelligence; Data science; Pandemic; Machine learning; Information retrieval; Computer security; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.07094410834294539,"gpt":0.4042123562395051,"spread":0.3332682478965597,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004448707,0.0002083612,0.002352905,0.0003002844,0.002250801,0.00009710153,0.0002743714,0.0001489595,0.0005448262],"category_scores_gemma":[0.001339714,0.0001837383,0.0009912888,0.003059212,0.00009666396,0.0001413148,0.00006597667,0.0001925082,0.00000267643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001786891,"about_ca_system_score_gemma":0.0005808431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001253516,"about_ca_topic_score_gemma":0.000161745,"domain_scores_codex":[0.9971107,0.0006838232,0.001295825,0.0001763754,0.0004452568,0.000288011],"domain_scores_gemma":[0.9963701,0.001082839,0.002107992,0.0001551109,0.00009196415,0.0001919318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001474822,0.00001020793,0.000002872504,0.6589534,0.001456914,1.454126e-7,0.01674087,0.00005755364,2.249006e-10,0.005108797,0.002554322,0.3151135],"study_design_scores_gemma":[0.00005967025,0.00001083147,1.27035e-7,0.01324721,0.01376088,6.315133e-7,0.004923487,0.000205948,2.932244e-10,0.00003563603,0.9675814,0.0001742023],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[6.454979e-8,0.9825722,0.01109186,0.0001218717,0.00003574699,0.002224914,0.00004758262,0.00004032499,0.00386543],"genre_scores_gemma":[0.000007447105,0.9966587,0.0003158203,0.0004782194,0.0002271171,0.0003875791,0.0008276968,0.00001320173,0.001084177],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.965027,"threshold_uncertainty_score":0.9990481,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3198016176","doi":"10.1007/s13278-021-00784-6","title":"Improving e-commerce product recommendation using semantic context and sequential historical purchases","year":2021,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Information retrieval; Context (archaeology); Semantics (computer science); Recommender system; Collaborative filtering; Similarity (geometry); Personalization; Cluster analysis; Semantic similarity; Process (computing); Metadata; Preprocessor; Matching (statistics); Natural language processing; Artificial intelligence; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.0382843593755317,"gpt":0.2797074508244983,"spread":0.2414230914489666,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000572888,0.0001398788,0.0004039007,0.0001103324,0.0005957352,0.0003068831,0.0001115424,0.00006494861,0.000008677941],"category_scores_gemma":[0.0000299022,0.0001416592,0.0001243687,0.0008460141,0.000025951,0.0002824219,0.0002587364,0.0001119528,1.835154e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001072526,"about_ca_system_score_gemma":0.0000465639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000867988,"about_ca_topic_score_gemma":0.0003897742,"domain_scores_codex":[0.9985987,0.0002189645,0.0003262282,0.0004720273,0.0001223824,0.0002617227],"domain_scores_gemma":[0.9993932,0.0000745518,0.000208157,0.0001620502,0.00009467309,0.00006737872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005308691,0.00004648027,0.02855223,0.00004892269,0.0006658223,0.00002187585,0.003060092,0.00003872633,0.000932328,0.003740786,0.002182141,0.9607053],"study_design_scores_gemma":[0.001615267,0.0002320114,0.01723065,0.0002430061,0.00359789,0.0002271327,0.004304765,0.8972244,0.001832719,0.003350991,0.0677964,0.002344802],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1090448,0.001955495,0.8862604,0.001946615,0.0003823382,0.00009661481,0.000001233191,0.0001020818,0.0002103985],"genre_scores_gemma":[0.9641332,0.00008071533,0.03486547,0.0002198856,0.0005563196,0.000006198848,0.0000124851,0.000008990115,0.000116736],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9583605,"threshold_uncertainty_score":0.5776696,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4293104636","doi":"10.1007/s13278-022-00948-y","title":"How coordinated link sharing behavior and partisans’ narrative framing fan the spread of COVID-19 misinformation and conspiracy theories","year":2022,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Canadian Institutes of Health Research; Canada Research Chairs; Compute Canada","keywords":"Misinformation; Hydroxychloroquine; Framing (construction); STELLA (programming language); Narrative; Government (linguistics); Political science; Media studies; Sociology; Coronavirus disease 2019 (COVID-19); Law; History; Computer science; Medicine; Art; Philosophy; Literature; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.02926600082102716,"gpt":0.3230010669898934,"spread":0.2937350661688662,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001528818,0.00009262883,0.000239242,0.0000955317,0.003888318,0.0003241592,0.00009356363,0.00005535803,0.00007708687],"category_scores_gemma":[0.0002885535,0.00007768417,0.00005683703,0.0008500257,0.0004282304,0.0003958146,0.0001127988,0.0001307378,6.466401e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003870897,"about_ca_system_score_gemma":0.0000975713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006685047,"about_ca_topic_score_gemma":0.0008102885,"domain_scores_codex":[0.9989458,0.0002246062,0.0002454533,0.00012226,0.0002471618,0.0002146902],"domain_scores_gemma":[0.9991773,0.0002519041,0.0003280602,0.00006364756,0.00006761368,0.000111464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002141848,0.000008025081,0.04092086,0.00001647343,0.000217361,8.633417e-7,0.888163,0.0002860181,0.000008866653,0.02996742,0.000342451,0.04004727],"study_design_scores_gemma":[0.000415064,0.00005183958,0.0221696,0.0000108069,0.0006455835,0.000001497451,0.9624206,0.003265216,0.000007384286,0.001645994,0.009170262,0.0001961562],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921219,0.0005165042,0.001553788,0.003883649,0.00005824239,0.0002072121,0.00001461534,0.00002634872,0.001617744],"genre_scores_gemma":[0.9989156,0.0001288306,0.00009317026,0.0004393754,0.000108811,0.000009992877,0.00002507766,0.00000381312,0.0002753755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07425763,"threshold_uncertainty_score":0.9974085,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4294571684","doi":"10.1007/s13278-022-00946-0","title":"Automatically detecting and understanding the perception of COVID-19 vaccination: a middle east case study","year":2022,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Pandemic; Sentiment analysis; Social media; Perception; Coronavirus disease 2019 (COVID-19); Arabic; Vaccination; Computer science; Data science; Internet privacy; Psychology; Medicine; Artificial intelligence; World Wide Web; Virology; Linguistics; Disease","retraction":null,"screen_n_in":null,"score":{"opus":0.08300221817925063,"gpt":0.3338486034082799,"spread":0.2508463852290293,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002096964,0.00007066426,0.0002141828,0.00009667575,0.005756468,0.00009344191,0.00007400019,0.00002979672,0.0002608945],"category_scores_gemma":[0.0001234238,0.00006327801,0.00008860837,0.001216306,0.00002601837,0.00008004953,0.0001036036,0.0001079249,9.22571e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001677265,"about_ca_system_score_gemma":0.00008435506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001405981,"about_ca_topic_score_gemma":0.01577421,"domain_scores_codex":[0.9985547,0.0005965782,0.0002274591,0.0001753958,0.0002618424,0.0001840034],"domain_scores_gemma":[0.9993525,0.0003133377,0.0001691675,0.00006242298,0.00003392556,0.00006863042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001829977,0.00005628106,0.2750177,0.00001581977,0.0004802895,0.00008748094,0.7082323,0.001541155,0.000002525213,0.004609321,0.0001704107,0.009768494],"study_design_scores_gemma":[0.000256496,0.00006530705,0.0190916,0.000002261467,0.0007326338,0.00001287787,0.9742672,0.004182485,1.21372e-8,0.001184825,0.000120895,0.00008342501],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920266,0.0001995428,0.005817168,0.0009701105,0.00004514002,0.0001848095,0.000001711403,0.0000245442,0.0007303472],"genre_scores_gemma":[0.9993665,0.00001757247,0.0001356466,0.0001280136,0.0002643955,0.00001622681,0.000001514446,0.00000496016,0.00006513161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2660349,"threshold_uncertainty_score":0.9955379,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200251175","doi":"10.1007/s13278-021-00834-z","title":"I tag, you tag: the role of tagging in the formation of topic-based communities of video game channels in YouTube (2016)","year":2021,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Digital Games and Media","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Computer science; Video game; Information retrieval; World Wide Web; Multimedia","retraction":null,"screen_n_in":null,"score":{"opus":0.01844916626947933,"gpt":0.2669945471486658,"spread":0.2485453808791864,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001188796,0.0000545312,0.0002687123,0.00007415841,0.0000975234,0.00003390328,0.0001472748,0.00004950748,0.00001546241],"category_scores_gemma":[0.00007306094,0.00003871731,0.0001252977,0.001014531,0.0002072702,0.0001054317,0.000036203,0.00007588782,5.701559e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001340902,"about_ca_system_score_gemma":0.00006882222,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001850086,"about_ca_topic_score_gemma":0.01866018,"domain_scores_codex":[0.9989621,0.0003040817,0.000303472,0.00005711555,0.0002106292,0.0001626218],"domain_scores_gemma":[0.9992991,0.0003094368,0.0002055263,0.00009236992,0.0000786075,0.00001493615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002155321,0.00008935659,0.1002863,0.00003854626,0.0001478505,0.000001472745,0.7209262,0.005934686,0.00003698016,0.01256615,0.00006709307,0.1598838],"study_design_scores_gemma":[0.000347832,0.00003375154,0.01799605,0.000171509,0.0002653593,1.116317e-7,0.9528211,0.008719847,0.00014833,0.001877428,0.01750213,0.0001164955],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809896,0.00112699,0.0001391897,0.0006409631,0.00005196401,0.00008044634,0.000005479236,0.000003036348,0.01696234],"genre_scores_gemma":[0.9993505,0.0002082123,0.00005657886,0.0001179972,0.0001199377,0.000005782179,0.0000148936,0.00000238872,0.0001237502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.231895,"threshold_uncertainty_score":0.9992467,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2963217293","doi":"10.1007/s13278-019-0567-9","title":"Characterizing the Twitter network of prominent politicians and SPLC-defined hate groups in the 2016 US presidential election","year":2019,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Social Media and Politics","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Uppsala Universitet","keywords":"Presidential election; Ideology; Population; Presidential system; Benford's law; Political science; Test (biology); Computer science; Politics; Sociology; Mathematics; Statistics; Law; Demography; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.01398059883982378,"gpt":0.2738386213686415,"spread":0.2598580225288177,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001126737,0.0001139342,0.0003274367,0.00004994381,0.0007318167,0.0001246802,0.0001434028,0.0001198099,0.00003110596],"category_scores_gemma":[0.00005407508,0.00007901101,0.0001341262,0.0008678736,0.0002503045,0.00009343877,0.00004322494,0.0001584485,0.000001510033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003453192,"about_ca_system_score_gemma":0.00007711697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004989543,"about_ca_topic_score_gemma":0.005949447,"domain_scores_codex":[0.9981719,0.000559364,0.0002949508,0.0001842537,0.0002812077,0.0005083454],"domain_scores_gemma":[0.9991356,0.0004634061,0.0002108273,0.0000905355,0.00005152217,0.00004810171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002979478,0.00001874131,0.8499899,0.00001479246,0.000347975,0.000001715826,0.1337851,0.00003067076,0.00008527811,0.01230751,0.0009078682,0.002480713],"study_design_scores_gemma":[0.0004459325,0.00007134424,0.9185912,0.00007474681,0.001228682,7.777678e-7,0.06054478,0.0003977596,0.00001798161,0.005526676,0.01282648,0.0002736521],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947923,0.0003331706,0.00003830532,0.002601894,0.0003435695,0.0002680444,0.000002142009,0.00001034446,0.001610267],"genre_scores_gemma":[0.9953892,0.0002627094,0.00004465507,0.0007096701,0.003314773,0.00001775892,0.000008157889,0.000008380921,0.0002446431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07324028,"threshold_uncertainty_score":0.7542729,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1977804969","doi":"10.1007/s13278-014-0171-y","title":"Social media analysis and summarization for opinion mining: a business case study","year":2014,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Bank of Canada; University of Calgary","funders":"","keywords":"Automatic summarization; Computer science; Social media; Diversity (politics); Subject (documents); Variety (cybernetics); Sentiment analysis; Data science; Microblogging; Public opinion; World Wide Web; Information retrieval; Internet privacy; Artificial intelligence; Sociology; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.02241678001222896,"gpt":0.3019833421825592,"spread":0.2795665621703302,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001000112,0.0003011834,0.001046873,0.0005058807,0.001367502,0.0002493642,0.0001171841,0.00009778723,0.00003463797],"category_scores_gemma":[0.00003038607,0.0003080423,0.0004744616,0.004582147,0.00009900428,0.000122454,0.0001415459,0.000102669,1.966695e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002039818,"about_ca_system_score_gemma":0.00002253822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007261156,"about_ca_topic_score_gemma":0.003160211,"domain_scores_codex":[0.9979235,0.0002649841,0.0005542965,0.0006077108,0.0002249977,0.0004245093],"domain_scores_gemma":[0.9985224,0.000511672,0.0004262186,0.0001807246,0.0002579138,0.0001010844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003120461,0.0001458293,0.8654226,0.00001177948,0.01029554,0.000004258205,0.00994713,0.001031093,0.000003967913,0.002244781,0.0009909268,0.1098709],"study_design_scores_gemma":[0.002860063,0.0002000928,0.493695,0.00003153324,0.08222649,0.000004590656,0.04628942,0.3634658,0.000005994347,0.005763859,0.003569881,0.001887304],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7620018,0.00007611433,0.2372685,0.00008417018,0.00005229646,0.0002308542,0.00001465851,0.00005753883,0.0002140575],"genre_scores_gemma":[0.9930955,0.000007932775,0.003513011,0.00002592208,0.002755763,0.00008525655,0.0004526621,0.00002730085,0.00003666765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3717276,"threshold_uncertainty_score":0.9999372,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3080086862","doi":"10.1007/s13278-020-00677-0","title":"Basketball lineup performance prediction using edge-centric multi-view network analysis","year":2020,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Ontario Tech University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Basketball; Computer science; Enhanced Data Rates for GSM Evolution; Analytics; Metric (unit); Artificial intelligence; Machine learning; Performance metric; Data science; Engineering; Operations management","retraction":null,"screen_n_in":null,"score":{"opus":0.04732602641377733,"gpt":0.236263666082216,"spread":0.1889376396684386,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008420647,0.0002830758,0.001174509,0.0003571659,0.0008027543,0.0001978227,0.0001926395,0.0001783005,0.0004430716],"category_scores_gemma":[0.00002448572,0.0003178961,0.0006395958,0.006591667,0.00006929979,0.0002561064,0.0001106956,0.0002345394,0.00001866543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006649459,"about_ca_system_score_gemma":0.00002557293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001487307,"about_ca_topic_score_gemma":0.0001329281,"domain_scores_codex":[0.9975528,0.00002984819,0.001014054,0.0006831491,0.00009986194,0.000620249],"domain_scores_gemma":[0.9987654,0.00003702629,0.0007082833,0.0002018955,0.00007305826,0.0002143484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001242522,0.00002034391,0.6967247,0.00002198851,0.002494826,0.000002069475,0.0005755027,0.2973796,3.030071e-7,0.0005162958,0.0004314325,0.001820575],"study_design_scores_gemma":[0.0002527905,0.00002848642,0.2499903,0.00001021985,0.002291461,3.203021e-7,0.00007815614,0.7368178,2.53738e-7,0.00003168335,0.01024117,0.0002573716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8844563,0.01000099,0.1031588,0.0003555968,0.0003964348,0.0002136944,0.00009334199,0.00008188305,0.001242912],"genre_scores_gemma":[0.9902434,0.00330834,0.003059711,0.0006984147,0.002288289,0.000008002754,0.0001417458,0.00002829082,0.00022375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4467344,"threshold_uncertainty_score":0.9999273,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2010994105","doi":"10.1007/s13278-015-0292-y","title":"SSRM: structural social role mining for dynamic social networks","year":2015,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Betweenness centrality; Centrality; Social network (sociolinguistics); Automatic summarization; Leverage (statistics); Data science; Social network analysis; Dynamic network analysis; Computer science; Organizational network analysis; Community structure; Event (particle physics); Network science; Complex network; Knowledge management; Artificial intelligence; Social media; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.01504564858370448,"gpt":0.2927856893137764,"spread":0.2777400407300719,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0007754621,0.0004243532,0.001090582,0.0002018003,0.00188595,0.000279432,0.000288537,0.0001995432,0.00008960757],"category_scores_gemma":[0.000009020401,0.0004479639,0.0009408921,0.001614447,0.0001793528,0.0001670184,0.0002155786,0.000262128,0.000001088636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009221749,"about_ca_system_score_gemma":0.00007282654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001937628,"about_ca_topic_score_gemma":0.0003933081,"domain_scores_codex":[0.9972867,0.0001856411,0.0006416427,0.0006272313,0.000324988,0.0009337928],"domain_scores_gemma":[0.9987766,0.0001509106,0.000508099,0.0001546937,0.0002377738,0.0001718792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003243895,0.0001260277,0.332154,0.00002354061,0.01425371,0.000004410177,0.02321171,0.02200725,0.00003543198,0.03419461,0.04479592,0.528869],"study_design_scores_gemma":[0.001862334,0.000115703,0.03961376,0.00002124529,0.008544947,8.523791e-7,0.01824575,0.8923367,0.000004777143,0.02976294,0.007939105,0.001551871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.817925,0.000684251,0.176095,0.0004343068,0.0002628725,0.0004206114,0.00006178203,0.0002386826,0.003877521],"genre_scores_gemma":[0.9864355,0.00000352136,0.005974858,0.00009908255,0.006477816,0.00008127838,0.0005532539,0.00005644025,0.000318211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8703294,"threshold_uncertainty_score":0.9997972,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2811039307","doi":"10.1007/s13278-018-0523-0","title":"Entity linking of tweets based on dominant entity candidates","year":2018,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Topic Modeling","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University; Thomson Reuters (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Entity linking; Computer science; Information retrieval; Annotation; Context (archaeology); Limiting; Process (computing); Space (punctuation); Natural language processing; Named entity; Artificial intelligence; Knowledge base","retraction":null,"screen_n_in":null,"score":{"opus":0.01306936156287621,"gpt":0.2553194528917092,"spread":0.242250091328833,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061621,0.00009380384,0.0002891888,0.0001260265,0.0003782272,0.00008572348,0.0002410175,0.00006005691,0.00001547492],"category_scores_gemma":[0.00002031895,0.00008758204,0.0001429213,0.0008284891,0.00007242068,0.0000951071,0.0001298163,0.00006897419,0.000001457263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001884644,"about_ca_system_score_gemma":0.00003507876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002221217,"about_ca_topic_score_gemma":0.0006813363,"domain_scores_codex":[0.9989431,0.00008005143,0.000235435,0.000296536,0.0002113125,0.0002335733],"domain_scores_gemma":[0.9994072,0.00008349511,0.0001702347,0.0002136687,0.00007977584,0.00004564412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004140082,0.0001184303,0.8225748,0.0000478205,0.0009512811,0.00001103271,0.01011904,0.01200668,0.0003558411,0.01446085,0.0005435405,0.1387693],"study_design_scores_gemma":[0.0002465386,0.00005964503,0.03100766,0.00004916949,0.0002304591,1.542157e-7,0.00007603291,0.9663835,0.0003127648,0.001047175,0.0004232334,0.0001636587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5030555,0.00005367395,0.4958434,0.00008817497,0.0001543033,0.00003104618,9.530967e-7,0.00001752091,0.0007555478],"genre_scores_gemma":[0.9811968,0.000007068285,0.01811351,0.0001243807,0.0005143532,0.000001739779,0.000003691083,0.000003598772,0.00003487962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9543768,"threshold_uncertainty_score":0.3571492,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2001724096","doi":"10.1007/s13278-014-0182-8","title":"Modeling dynamic social networks using spectral embedding","year":2014,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Queen's University","funders":"","keywords":"Computer science; Embedding; Dynamic network analysis; Theoretical computer science; Social network (sociolinguistics); Graph drawing; Graph; Network science; Set (abstract data type); Node (physics); Complex network; Social media; Artificial intelligence; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.01290722716320876,"gpt":0.2906071255030344,"spread":0.2776998983398256,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0007435976,0.0003375532,0.0008635762,0.0002251204,0.001581016,0.000234075,0.0002016658,0.0001208639,0.0001358307],"category_scores_gemma":[0.000003974371,0.0003662333,0.0007045881,0.001649241,0.00008890759,0.0001383915,0.0001728186,0.0003080151,0.000001030365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005886212,"about_ca_system_score_gemma":0.00002093706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000353038,"about_ca_topic_score_gemma":0.0002065245,"domain_scores_codex":[0.997695,0.000210145,0.0005437375,0.0005446455,0.0002389434,0.0007675217],"domain_scores_gemma":[0.9992976,0.00008180331,0.0002554379,0.0001771197,0.0000816148,0.0001064119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001237998,0.00002860681,0.03560766,0.000004059095,0.002041359,8.017388e-7,0.0007966129,0.9157835,0.00002898957,0.008881829,0.0001618948,0.03665228],"study_design_scores_gemma":[0.0001758999,0.00001108398,0.001352696,0.00001447455,0.002302579,2.867711e-7,0.0005854059,0.9903951,0.000001124219,0.004659343,0.0001107766,0.0003912178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4087086,0.00009349542,0.5898613,0.00003172512,0.00004864002,0.00005496079,0.000001934493,0.00007256936,0.001126724],"genre_scores_gemma":[0.9833604,0.000007738828,0.01255942,0.00005958841,0.003814529,0.000009448605,0.00008828189,0.00004288015,0.00005779023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5773019,"threshold_uncertainty_score":0.9998789,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3046139311","doi":"10.1007/s13278-020-00661-8","title":"YouTube of porn: longitudinal measurement, analysis, and characterization of a large porn streaming service","year":2020,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Sexuality, Behavior, and Technology","field":"Psychology","cited_by":12,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of New Brunswick","funders":"","keywords":"Upload; Computer science; Entertainment; Service (business); World Wide Web; Social media; Amateur; Multimedia; Metadata; The Internet; Live streaming; Internet privacy; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.0542304332042697,"gpt":0.3193298679728465,"spread":0.2650994347685768,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000551091,0.0001575192,0.0007784482,0.0002637683,0.0001570119,0.00001668585,0.0001079218,0.0001858912,0.000142269],"category_scores_gemma":[0.0000205281,0.0001632104,0.0001889467,0.003189194,0.00007539467,0.00005399858,0.00008566346,0.0001153395,5.413501e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001137348,"about_ca_system_score_gemma":0.00001635608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000432703,"about_ca_topic_score_gemma":0.00164316,"domain_scores_codex":[0.9984421,0.0001486871,0.0005120081,0.0003926907,0.0002267616,0.0002777299],"domain_scores_gemma":[0.9990319,0.00003326824,0.0004973156,0.0001584519,0.0002086858,0.00007036763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005233687,0.0000871116,0.9742014,0.00002617602,0.00522356,0.00000443119,0.00898161,0.000006821219,0.002564039,0.001282782,0.00001885869,0.007550857],"study_design_scores_gemma":[0.0004867695,0.0000785942,0.9821176,0.00001004964,0.01066823,6.27251e-7,0.005428487,0.0007123653,0.00009467811,0.00002951925,0.0002086062,0.0001644953],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935584,0.0003529532,0.005290048,0.0002771661,0.00005091022,0.00007841017,0.00005253829,0.00003123372,0.0003083281],"genre_scores_gemma":[0.9992173,0.00003260058,0.0001558398,0.000164571,0.0001989279,0.000006032109,0.0001820723,0.00001164513,0.00003105053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007916164,"threshold_uncertainty_score":0.6655526,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2005763451","doi":"10.1007/s13278-015-0248-2","title":"Towards intelligent control of influence diffusion in social networks","year":2015,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Diffusion; Control (management); Computer science; Distributed computing; Artificial intelligence; Physics; Quantum mechanics","retraction":null,"screen_n_in":null,"score":{"opus":0.01327398360352782,"gpt":0.2782857137629465,"spread":0.2650117301594186,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005178391,0.0001429054,0.0005234957,0.00009750335,0.0002251244,0.00004569451,0.0001159927,0.00009120037,0.00002141634],"category_scores_gemma":[0.000009500784,0.0001430843,0.0002101841,0.001008784,0.0001204712,0.00007827374,0.00007820848,0.0001542055,5.467337e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002953596,"about_ca_system_score_gemma":0.00005773817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001005584,"about_ca_topic_score_gemma":0.0001335321,"domain_scores_codex":[0.9987655,0.0001132717,0.0004203241,0.0002114913,0.0001842066,0.0003052087],"domain_scores_gemma":[0.9994185,0.00005355587,0.0002435058,0.00006915744,0.0001291886,0.00008612363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003577511,0.00006153117,0.8690482,0.000003895888,0.0004337592,9.033652e-7,0.005112098,0.05978936,0.000006818829,0.02954751,0.0001083631,0.03585177],"study_design_scores_gemma":[0.001939285,0.0000934555,0.6255223,0.00005549654,0.0009189369,1.19904e-7,0.01023729,0.3429925,0.000004901013,0.01653088,0.001049893,0.000655018],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9464662,0.0001948354,0.05135882,0.0001148414,0.00009262601,0.00009341774,0.00001149554,0.000009506719,0.00165823],"genre_scores_gemma":[0.9988932,0.00001717855,0.0001963421,0.0000727536,0.0007452046,0.0000100592,0.00002507943,0.000008985114,0.00003116887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2832031,"threshold_uncertainty_score":0.583481,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2056007251","doi":"10.1007/s13278-013-0132-x","title":"Communities validity: methodical evaluation of community mining algorithms","year":2013,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Alberta Innovates; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Cluster analysis; Data mining; Computer science; Context (archaeology); Set (abstract data type); Graph; Machine learning; Theoretical computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.1065850968644788,"gpt":0.3637313854001314,"spread":0.2571462885356527,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003908866,0.0001988712,0.0007333775,0.0001982122,0.001004983,0.0001103459,0.0002460957,0.00007681373,0.000919782],"category_scores_gemma":[0.00001794026,0.0001988657,0.0004072519,0.001246266,0.0002199852,0.0001416342,0.0002434089,0.000308205,0.000001330559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002764722,"about_ca_system_score_gemma":0.0000389151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006201035,"about_ca_topic_score_gemma":0.0004983172,"domain_scores_codex":[0.9962696,0.002314441,0.0005225608,0.0001342146,0.0004423253,0.0003168704],"domain_scores_gemma":[0.9981033,0.0006899554,0.0003916798,0.0003182213,0.0004226951,0.00007418874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006058328,0.0001540035,0.4350511,0.00001119123,0.004046056,9.416435e-8,0.01570967,0.003089737,0.00003587011,0.002371812,0.003511109,0.5360134],"study_design_scores_gemma":[0.0008565137,0.0001195648,0.2682338,0.0000720343,0.01639188,4.123005e-7,0.09320736,0.5744577,0.0001139747,0.04514747,0.0006053413,0.0007939779],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9440397,0.0001482214,0.05104261,0.00006631516,0.00002996467,0.0001598689,0.000007103446,0.00003935475,0.004466873],"genre_scores_gemma":[0.9821806,0.000008278708,0.01700887,0.00004359008,0.0004560671,0.00006585289,0.0001863935,0.00001526709,0.00003509746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.571368,"threshold_uncertainty_score":0.9999935,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4390541142","doi":"10.1007/s13278-023-01178-6","title":"Review of heterogeneous graph embedding methods based on deep learning techniques and comparing their efficiency in node classification","year":2024,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Mount Royal University","funders":"","keywords":"Embedding; Graph embedding; Computer science; Graph; Cluster analysis; Theoretical computer science; Clustering coefficient; Artificial intelligence; Machine learning; Data mining","retraction":null,"screen_n_in":null,"score":{"opus":0.02837100555435484,"gpt":0.345334446618343,"spread":0.3169634410639882,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001215569,0.0001606414,0.0004786374,0.0003529176,0.0002172654,0.00008743423,0.0001843046,0.00006789504,0.000001273361],"category_scores_gemma":[0.00002280712,0.000142363,0.0001740814,0.002964089,0.00007057049,0.0001190125,0.00009780432,0.000242137,7.809943e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002264578,"about_ca_system_score_gemma":0.000009340104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005250634,"about_ca_topic_score_gemma":0.00001169407,"domain_scores_codex":[0.9984017,0.0003785611,0.0003859207,0.0004524592,0.0001280825,0.000253271],"domain_scores_gemma":[0.9991788,0.0004194684,0.0001663806,0.000156466,0.00003640358,0.00004249034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008215315,0.00002195348,0.01098869,0.0005379181,0.0001445196,0.00001202087,0.0010452,0.1286609,0.0001734419,0.002749314,0.00001563006,0.8556423],"study_design_scores_gemma":[0.00005089912,0.00003596479,0.0007614667,0.001765313,0.0000959936,0.000002056758,0.00004685307,0.9961183,0.00006782894,0.0006273287,0.0002832367,0.0001447772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01371463,0.06875804,0.916912,0.0001201763,0.00005467742,0.0001150515,2.439031e-7,0.0001196417,0.0002055641],"genre_scores_gemma":[0.8592403,0.01162381,0.128871,0.0001553242,0.00007422924,0.00001694939,0.000005247329,0.00001110593,0.000002032096],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8674574,"threshold_uncertainty_score":0.5805396,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2059645366","doi":"10.1007/s13278-012-0071-y","title":"Managing node disappearance based on information flow in social networks","year":2012,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Node (physics); Computer science; Exploit; Information flow; Quality (philosophy); Social network (sociolinguistics); Flow (mathematics); Flow network; Computer network; Restructuring; Distributed computing; Data mining; Computer security; World Wide Web; Mathematics; Mathematical optimization","retraction":null,"screen_n_in":null,"score":{"opus":0.008356677030947312,"gpt":0.2531741437393,"spread":0.2448174667083527,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006736011,0.0002213249,0.0004942971,0.0002786179,0.0006057699,0.0001213523,0.0001227374,0.00007897161,0.0001104786],"category_scores_gemma":[0.000003087756,0.0002316491,0.0003247073,0.001907021,0.00005475821,0.0003328439,0.00006826762,0.0002392073,0.000003771141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004614922,"about_ca_system_score_gemma":0.0000117439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001228195,"about_ca_topic_score_gemma":0.00005458846,"domain_scores_codex":[0.9984096,0.0001386293,0.0004187061,0.0001999748,0.0002135351,0.0006195329],"domain_scores_gemma":[0.9994351,0.00008578958,0.0002353269,0.0001324214,0.00003553692,0.00007582812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003213085,0.00006102471,0.5663887,0.000005713698,0.0004181287,3.134247e-7,0.001357586,0.2366738,4.251116e-7,0.004575484,0.001966026,0.1885207],"study_design_scores_gemma":[0.0003030043,0.000008691429,0.1174842,0.0000256396,0.0005229793,2.934934e-8,0.0005313329,0.8776518,0.000001057502,0.0007714598,0.002401988,0.0002978305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1368952,0.0002567977,0.8394508,0.0005545586,0.0001633497,0.0002582321,0.00001291867,0.0001379733,0.02227012],"genre_scores_gemma":[0.9946816,0.000007093587,0.002483073,0.0003042243,0.002261724,0.00003336302,0.0001910408,0.00001451223,0.00002337364],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8577864,"threshold_uncertainty_score":0.9446376,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2541641307","doi":"10.1007/s13278-017-0424-7","title":"Hashkat: large-scale simulations of online social networks","year":2017,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada; Toronto Metropolitan University; University of Waterloo; Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Python (programming language); Scripting language; Social network (sociolinguistics); Extensibility; Software; Network topology; Dynamic network analysis; Social computing","retraction":null,"screen_n_in":null,"score":{"opus":0.01670620556944801,"gpt":0.3100303740819892,"spread":0.2933241685125412,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003563109,0.0002121655,0.0007641932,0.0001227853,0.002426624,0.0001644357,0.0003047031,0.0001000291,0.0002848229],"category_scores_gemma":[0.000006743418,0.0002210297,0.0005965301,0.0006096817,0.0001887658,0.0001332417,0.000271047,0.000190328,5.039435e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001324793,"about_ca_system_score_gemma":0.00002454964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002745111,"about_ca_topic_score_gemma":0.001588115,"domain_scores_codex":[0.9984564,0.00008926373,0.0004807513,0.0003389066,0.0001920686,0.0004426661],"domain_scores_gemma":[0.9986742,0.00009303579,0.0006950545,0.000329677,0.0001376703,0.00007033178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001965189,0.000204463,0.9114384,0.000005638793,0.003405696,8.465852e-7,0.001680035,0.02353352,0.00001578249,0.008386551,0.002699083,0.04861031],"study_design_scores_gemma":[0.0006047547,0.00002576909,0.3865345,0.00002447353,0.004471923,7.646359e-8,0.001381829,0.5982209,0.000007608824,0.004860475,0.003395633,0.0004720389],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7912406,0.0001767495,0.2039433,0.0003102487,0.00008425448,0.0001396184,0.000133269,0.00006031789,0.003911701],"genre_scores_gemma":[0.9932788,0.000009826162,0.003295546,0.00003488592,0.002808573,0.000006318983,0.0003226647,0.00002074846,0.0002226179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5746874,"threshold_uncertainty_score":0.9988721,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3024970747","doi":"10.1007/s13278-020-00644-9","title":"A new approach for affinity relationship discovery in online forums","year":2020,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université TÉLUQ; Université de Sherbrooke","funders":"","keywords":"Context (archaeology); Markov chain; Computer science; Affinity maturation; Machine learning; Data mining; Chemistry; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.04226712464845622,"gpt":0.2959836247082475,"spread":0.2537165000597913,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002632932,0.0001570156,0.0005057045,0.00009883117,0.0002714418,0.0001059029,0.0001223927,0.00005629408,0.00004409667],"category_scores_gemma":[0.00001677245,0.0001606629,0.0003898743,0.00173059,0.00002710822,0.0001365478,0.00008650778,0.0001601668,4.238368e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001577381,"about_ca_system_score_gemma":0.00004021913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002421331,"about_ca_topic_score_gemma":0.0002933297,"domain_scores_codex":[0.9988102,0.00007253766,0.000348612,0.0003596569,0.0001051082,0.0003038325],"domain_scores_gemma":[0.9994153,0.0001924999,0.0001666405,0.0001032672,0.00002708655,0.00009523259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004355204,0.00005959853,0.9318051,0.000008292334,0.0008359227,2.8273e-7,0.001442361,0.01218534,0.000004583902,0.02156559,0.006414501,0.02563492],"study_design_scores_gemma":[0.001772944,0.00009716688,0.2692701,0.00003130276,0.004866997,1.22029e-7,0.007020226,0.6765735,0.000008835879,0.03503321,0.004305185,0.001020428],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1386641,0.0001224977,0.8587719,0.0005340075,0.00001208676,0.0001950118,0.00002666955,0.00004085789,0.0016329],"genre_scores_gemma":[0.9383785,0.000003801835,0.05911412,0.0001307828,0.0016176,0.00002488832,0.0005151462,0.00001475339,0.0002004181],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7997144,"threshold_uncertainty_score":0.6551641,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4392968283","doi":"10.1007/s13278-024-01219-8","title":"Text classification models for personality disorders identification","year":2024,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Mental Health via Writing","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Identification (biology); Personality disorders; Computer science; Personality; Psychology; Artificial intelligence; Natural language processing; Information retrieval; Pattern recognition (psychology); Data science; Social psychology; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.069153266633536,"gpt":0.3940855338709143,"spread":0.3249322672373783,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008859388,0.00008908709,0.0001853886,0.0001012623,0.000492222,0.00009438235,0.00005070268,0.00009445023,0.00009544363],"category_scores_gemma":[0.000008449604,0.00009485963,0.000171746,0.0007246975,0.0000398722,0.00009410973,0.00001386681,0.00008139058,0.000008010421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000483767,"about_ca_system_score_gemma":0.00001616808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001345848,"about_ca_topic_score_gemma":0.0003409846,"domain_scores_codex":[0.9988549,0.0001029278,0.0003104157,0.0003660673,0.0001055078,0.00026018],"domain_scores_gemma":[0.9995538,0.0001930097,0.00009826425,0.00007826757,0.00002921271,0.00004745689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005914626,0.00006125254,0.01738122,0.0001916188,0.001572524,8.438452e-7,0.02445491,0.000461115,0.00005551034,0.2480613,0.007947198,0.6997534],"study_design_scores_gemma":[0.0003202221,0.0000398571,0.1592443,0.00004845959,0.001960479,7.934212e-7,0.0227066,0.7822779,0.000001256027,0.02679779,0.006281151,0.0003211811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5334042,0.006346807,0.4364161,0.002906706,0.00104276,0.0006401047,0.00005956743,0.0002050593,0.01897871],"genre_scores_gemma":[0.997023,0.0000437473,0.0007049037,0.0001083492,0.0007474677,0.0001357215,0.0001517443,0.00001545728,0.001069609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7818168,"threshold_uncertainty_score":0.3868263,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4386419832","doi":"10.1007/s13278-023-01115-7","title":"Fast local community discovery relying on the strength of links","year":2023,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Alberta Machine Intelligence Institute; Canadian Institute for Advanced Research","keywords":"Computer science; Node (physics); Graph; Set (abstract data type); Data mining; Community structure; Theoretical computer science; Outlier; Artificial intelligence; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.02454573867931035,"gpt":0.2811854526579256,"spread":0.2566397139786152,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009174288,0.0001580496,0.000457061,0.000139606,0.001018931,0.00008208782,0.0002227805,0.00006927353,0.0000642423],"category_scores_gemma":[0.000008577496,0.0001206795,0.0004173664,0.0023151,0.0001774285,0.00006115669,0.0002183253,0.000515186,0.000002210998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000135559,"about_ca_system_score_gemma":0.00001671037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006244042,"about_ca_topic_score_gemma":0.0002522106,"domain_scores_codex":[0.9986445,0.0003574787,0.0003298011,0.000178652,0.0001945113,0.0002950754],"domain_scores_gemma":[0.9987165,0.0006875502,0.0002342478,0.0002791869,0.00004574175,0.00003681162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005765607,0.00023038,0.5149264,0.00002175809,0.008720102,0.000002303016,0.00984957,0.0328242,0.00008437054,0.130432,0.01605253,0.2867988],"study_design_scores_gemma":[0.001059063,0.0003562885,0.3641564,0.0004007612,0.01060874,3.082512e-7,0.1211582,0.42897,0.0005574676,0.06651773,0.004427138,0.001787873],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693747,0.00003731169,0.02509997,0.000217684,0.00002903282,0.00007642204,0.00001675842,0.00006299401,0.005085169],"genre_scores_gemma":[0.9988829,0.00001552612,0.0001771101,0.00005690444,0.0004815958,0.00001460479,0.0001129037,0.00001410185,0.0002442851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3961458,"threshold_uncertainty_score":0.7836895,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3194347029","doi":"10.1007/s13278-021-00785-5","title":"Multi-source based movie recommendation with ratings and the side information","year":2021,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"MovieLens; Computer science; Recommender system; Collaborative filtering; Variety (cybernetics); Information retrieval; Trailer; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01142841721809073,"gpt":0.232922560340746,"spread":0.2214941431226553,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006805584,0.00008056947,0.0002077512,0.00005235282,0.0004889321,0.0003838791,0.0000810878,0.00003890038,0.000003503227],"category_scores_gemma":[0.00001985789,0.00005412496,0.00005999432,0.0007191594,0.00003741208,0.0003407676,0.00007937353,0.00006949146,2.270315e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001014509,"about_ca_system_score_gemma":0.00002464396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001168718,"about_ca_topic_score_gemma":0.0003495605,"domain_scores_codex":[0.9992612,0.0001705102,0.0002064991,0.0001437764,0.00009228757,0.000125751],"domain_scores_gemma":[0.9994579,0.0001439838,0.0001844102,0.0001051984,0.00008050712,0.00002800417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000259904,0.00002263987,0.0291397,0.00002946713,0.0007317215,0.000002492747,0.01426676,0.001344627,0.00001385316,0.007781399,0.001874572,0.9447668],"study_design_scores_gemma":[0.001058435,0.00002480175,0.0116213,0.00002896322,0.0002547919,0.000004167358,0.001606929,0.9690689,0.00004373432,0.0002252181,0.01587695,0.0001858123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007960537,0.0001060859,0.9881495,0.003030147,0.00002950841,0.00007303841,5.355736e-7,0.00005115748,0.0005994381],"genre_scores_gemma":[0.8690384,0.00003540494,0.1294202,0.001310887,0.00008899852,0.00001955121,0.00002579227,0.000003516682,0.00005728767],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9677243,"threshold_uncertainty_score":0.376052,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2507508039","doi":"10.1007/s13278-016-0387-0","title":"Spectral embedding of directed networks","year":2016,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Embedding; Computer science; Artificial intelligence; Theoretical computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.008791855830323792,"gpt":0.2654640255222757,"spread":0.2566721696919519,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003542545,0.0001891441,0.0006447822,0.0001593838,0.0002721926,0.00003578111,0.0001378632,0.00005943127,0.0004701264],"category_scores_gemma":[0.000005196006,0.0001447277,0.000475089,0.001500986,0.0001167196,0.00008026406,0.0001015982,0.0000844249,8.393589e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001772653,"about_ca_system_score_gemma":0.00001411659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001270152,"about_ca_topic_score_gemma":0.00008022787,"domain_scores_codex":[0.9985804,0.0001065849,0.0004263365,0.0003164794,0.000154552,0.0004156665],"domain_scores_gemma":[0.9991638,0.0001958558,0.0003134038,0.0001728679,0.00007885639,0.00007522416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002325259,0.00004371264,0.8512701,0.000003044339,0.003876072,0.000001153493,0.0003825493,0.003361365,0.0001880567,0.01453491,0.002695074,0.1236207],"study_design_scores_gemma":[0.00228393,0.0002056905,0.5316684,0.000356955,0.01702231,0.000001214807,0.001864413,0.4012669,0.000586793,0.03595192,0.006301172,0.002490352],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6409741,0.0003022156,0.3528338,0.0001037413,0.00006084057,0.00009257303,0.000009493876,0.000132404,0.005490824],"genre_scores_gemma":[0.9938089,0.00002931314,0.004479557,0.00001491445,0.001346443,0.000009599473,0.00002160004,0.00001747955,0.0002722046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3979055,"threshold_uncertainty_score":0.5901825,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1972778893","doi":"10.1007/s13278-010-0016-2","title":"Introduction to the first issue of Social Network Analysis and Mining journal","year":2010,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Publication; Multidisciplinary approach; Computer science; Popularity; Variety (cybernetics); Data science; Field (mathematics); Social network (sociolinguistics); Social media; Management science; Engineering; Political science; World Wide Web; Sociology; Social science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.006249649551441206,"gpt":0.2553527334439966,"spread":0.2491030838925554,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001630623,0.0002980072,0.00101795,0.000388819,0.002177176,0.0002967822,0.0002865378,0.0001193584,0.0006528662],"category_scores_gemma":[0.00001876769,0.0002500519,0.0007712367,0.005091371,0.0001913521,0.0001248839,0.0002325986,0.0004738015,0.000001821972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001930928,"about_ca_system_score_gemma":0.00003079999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002496798,"about_ca_topic_score_gemma":0.002832566,"domain_scores_codex":[0.9977099,0.0001762088,0.0007222006,0.0004864519,0.0003358677,0.0005693677],"domain_scores_gemma":[0.9985346,0.0001808439,0.0006505329,0.0002714398,0.0002241883,0.0001383934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006718489,0.00007937972,0.7031475,0.000009550296,0.01995282,0.000001811598,0.009537964,0.02007051,0.00006684701,0.005799976,0.1158621,0.1254043],"study_design_scores_gemma":[0.0008050912,0.0001748148,0.4788294,0.00003416643,0.05554188,0.000005079389,0.009157572,0.04855653,0.00005547707,0.004800789,0.4005352,0.00150402],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414302,0.0002932835,0.04959084,0.006738011,0.0003822161,0.0002039664,0.00001364559,0.00005070875,0.001297105],"genre_scores_gemma":[0.9687836,0.00002143619,0.006617471,0.0001576449,0.02407254,0.00001757141,0.00005307123,0.00002352653,0.0002531169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2846731,"threshold_uncertainty_score":0.9999952,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403417412","doi":"10.1007/s13278-024-01356-0","title":"Predicting customer sentiment: the fusion of deep learning and a fuzzy system for sentiment analysis of Arabic text","year":2024,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"","keywords":"Sentiment analysis; Artificial intelligence; Arabic; Natural language processing; Computer science; Deep learning; Fusion; Fuzzy logic; Machine learning; Linguistics; Philosophy","retraction":null,"screen_n_in":null,"score":{"opus":0.01004847715716661,"gpt":0.2594210810814858,"spread":0.2493726039243191,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001654219,0.0001973657,0.0007941391,0.0007343282,0.0006248535,0.0002493262,0.0002217567,0.00008501577,0.00001516911],"category_scores_gemma":[0.00001873016,0.0001492197,0.0007476611,0.005183165,0.0000907246,0.0001615789,0.0002516006,0.0001216821,6.126417e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003082695,"about_ca_system_score_gemma":0.0000184988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005968515,"about_ca_topic_score_gemma":0.00005912362,"domain_scores_codex":[0.9978515,0.0001970116,0.00070258,0.0005245233,0.0003983182,0.0003260947],"domain_scores_gemma":[0.9986557,0.0005027275,0.0004598625,0.000190635,0.0001270683,0.00006395615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005279373,0.00009820994,0.5324823,0.0005706092,0.07072496,0.000009027866,0.04201293,0.08125691,0.0012179,0.02956769,0.0002394561,0.2417672],"study_design_scores_gemma":[0.0001696781,0.00003664023,0.01015051,0.00009645773,0.01409603,7.996056e-7,0.004822357,0.9699427,0.00007228194,0.00003923694,0.0004147633,0.0001585226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7243676,0.009888084,0.2638491,0.0002387539,0.000303297,0.0002957945,0.00000834353,0.0001072333,0.0009418072],"genre_scores_gemma":[0.9960053,0.0001562269,0.003405613,0.00001416545,0.0002010381,0.0000169449,0.00002645913,0.00001128757,0.0001629581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8886858,"threshold_uncertainty_score":0.6085004,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2032775730","doi":"10.1007/s13278-011-0022-z","title":"Introduction to the second issue of Social Network Analysis and Mining journal: scientific computing for social network analysis and dynamicity","year":2011,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Social network analysis; Computer science; Data science; Social network (sociolinguistics); Network analysis; World Wide Web; Social media; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01478354182322359,"gpt":0.2721317396699832,"spread":0.2573481978467596,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.004209361,0.0005454398,0.002133057,0.0009278361,0.006358478,0.0008304775,0.0004153817,0.0002056217,0.0004068942],"category_scores_gemma":[0.00002437917,0.000502427,0.00161343,0.01195445,0.0005826426,0.0002243599,0.0004505013,0.0004335874,6.846293e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006968001,"about_ca_system_score_gemma":0.00006656128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003621375,"about_ca_topic_score_gemma":0.004502627,"domain_scores_codex":[0.9953611,0.0005880541,0.001353203,0.00109708,0.0004756238,0.001124886],"domain_scores_gemma":[0.9970396,0.0003770113,0.001502104,0.0003496235,0.0005108847,0.0002207524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001619565,0.0001299085,0.7643952,0.00003997246,0.06376178,0.000001915985,0.02681388,0.0319339,0.00003390135,0.003426656,0.03491212,0.07438882],"study_design_scores_gemma":[0.0009724013,0.000195631,0.5590561,0.00004263211,0.1157033,0.000002316614,0.01170845,0.2846446,0.00002794389,0.007162191,0.01885451,0.001629971],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7604043,0.000441825,0.2376676,0.0005422675,0.0002483811,0.0003238692,0.0000490121,0.00005065481,0.0002721003],"genre_scores_gemma":[0.968456,0.00001436542,0.01714246,0.0001165084,0.01355156,0.0000259913,0.0002558671,0.00004482353,0.0003924159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2527107,"threshold_uncertainty_score":0.9997427,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4405382147","doi":"10.1007/s13278-024-01402-x","title":"Modeling interactions in social media networks using an asynchronous and synchronous opinion dynamics","year":2024,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Social media; Public opinion; Computer science; Convergence (economics); Asynchronous communication; Dynamics (music); Process (computing); Social network (sociolinguistics); Contrast (vision); Data science; Social dynamics; Public relations; Internet privacy; Artificial intelligence; Political science; Sociology; World Wide Web; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.0213299164842873,"gpt":0.3105252235034197,"spread":0.2891953070191324,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003395969,0.0002047094,0.0004256962,0.0001996461,0.0007815058,0.0003556746,0.00007963042,0.00009169434,0.0000272686],"category_scores_gemma":[0.000003525627,0.000227471,0.0001723923,0.0009628488,0.00008916342,0.0003014753,0.00008664607,0.0003212185,4.084943e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001070115,"about_ca_system_score_gemma":0.00006138218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001111356,"about_ca_topic_score_gemma":0.002066059,"domain_scores_codex":[0.9986094,0.0001026564,0.0003740023,0.0004036109,0.0001179296,0.0003924441],"domain_scores_gemma":[0.9996058,0.0001126069,0.00007703742,0.00007231925,0.00004392521,0.00008828174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001395584,0.00007445253,0.05457383,0.00002405308,0.0009879215,0.000005250943,0.0121711,0.7427038,0.00000568003,0.06783297,0.00002053009,0.1215865],"study_design_scores_gemma":[0.0001155459,0.000008192223,0.003069691,0.00004973285,0.0002862391,5.667659e-7,0.004704602,0.988438,5.92199e-8,0.00306225,0.00002757801,0.0002375125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7583452,0.0006459577,0.2400234,0.00006035975,0.0004514929,0.00007209036,0.0000253129,0.00003705115,0.000339061],"genre_scores_gemma":[0.9956247,0.00007883817,0.0009681522,0.00002089902,0.003060461,0.000009396028,0.0002044132,0.00002637167,0.000006789335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2457342,"threshold_uncertainty_score":0.9275999,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3131544549","doi":"10.1007/s13278-020-00714-y","title":"ShortWalk: an approach to network embedding on directed graphs","year":2021,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Random walk; Embedding; Computer science; Node (physics); Theoretical computer science; Graph; Random graph; Directed graph; Graph embedding; Algorithm; Artificial intelligence; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01799660246202238,"gpt":0.2767699594428392,"spread":0.2587733569808168,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004763315,0.0002994566,0.0006323985,0.0001953847,0.001048238,0.0003456099,0.0004615292,0.0001448572,0.000007222702],"category_scores_gemma":[0.00002925124,0.0003038141,0.0003205894,0.007668957,0.00005237032,0.0003017297,0.0003356007,0.0002773935,0.000001771207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002896392,"about_ca_system_score_gemma":0.00003022622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000117385,"about_ca_topic_score_gemma":0.0001271455,"domain_scores_codex":[0.997063,0.0003094548,0.000382132,0.001036759,0.0003694466,0.0008392113],"domain_scores_gemma":[0.9987357,0.0001859017,0.0001508101,0.0004997195,0.0001293193,0.0002985944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000393262,0.0001336373,0.02786937,0.000007484166,0.001147145,0.00006341361,0.002813915,0.7461368,0.00003078785,0.08581671,0.004219401,0.131722],"study_design_scores_gemma":[0.0003482314,0.0001620517,0.04791396,0.0000519941,0.0006741186,0.000009639411,0.000537106,0.9344607,0.00001233371,0.01184919,0.002968701,0.001011966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1910493,0.001006454,0.8003185,0.0003334382,0.0006994222,0.0002139272,0.000003209687,0.0006121608,0.005763612],"genre_scores_gemma":[0.7769804,0.00007124234,0.2200762,0.001481607,0.001129003,0.00002661965,0.00006175968,0.00002674636,0.0001463925],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5859311,"threshold_uncertainty_score":0.9999414,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4387105208","doi":"10.1007/s13278-023-01134-4","title":"Economic hubs and the domination of inter-regional ties in world city networks","year":2023,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Global Urban Networks and Dynamics","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Multinational corporation; Economic geography; Context (archaeology); Position (finance); Economic integration; Business; Economic system; Regional science; Economy; Geography; International trade; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.01566537711916016,"gpt":0.2774886149653585,"spread":0.2618232378461984,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00182515,0.00008533681,0.0003311901,0.0001495147,0.0005138349,0.00007649845,0.0001023364,0.0000825105,0.00002020275],"category_scores_gemma":[0.00002462676,0.00007110788,0.0001328511,0.001445937,0.0005886749,0.0000776637,0.00007833341,0.000103911,4.339867e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004557311,"about_ca_system_score_gemma":0.00002848209,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002698185,"about_ca_topic_score_gemma":0.128235,"domain_scores_codex":[0.9989374,0.0002400661,0.0002687486,0.0001708956,0.000110367,0.0002725473],"domain_scores_gemma":[0.999252,0.0004534555,0.0001683192,0.00005655471,0.0000283703,0.00004131253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001356477,0.00001413999,0.6323798,0.00000641138,0.0005510168,0.000002283402,0.0257966,0.09106605,1.176529e-7,0.2041229,0.008545017,0.03738002],"study_design_scores_gemma":[0.001149761,0.00001570447,0.297453,0.00004967128,0.0005949755,2.07634e-7,0.02057661,0.6550459,3.911653e-8,0.0175596,0.007279779,0.000274733],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871413,0.001078369,0.001568611,0.002403942,0.0002726198,0.0001670343,0.000003864233,0.00003334715,0.0073309],"genre_scores_gemma":[0.9976665,0.0008909064,0.00007295783,0.00009949646,0.0006010598,0.000007728493,0.00001569228,0.000004483827,0.0006411117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5639798,"threshold_uncertainty_score":0.8876725,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3126404394","doi":"10.1007/s13278-020-00718-8","title":"Modeling signed social networks using spectral embedding","year":2021,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Embedding; Computer science; Mathematics; Theoretical computer science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.02091834671576063,"gpt":0.2982792934682404,"spread":0.2773609467524797,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0004724358,0.0003226406,0.0008876451,0.000159065,0.001607411,0.000297367,0.0001521598,0.000124859,0.0003872081],"category_scores_gemma":[0.000004593163,0.0003684064,0.0008287889,0.002454745,0.00007218731,0.0001460815,0.0002221231,0.0002971407,8.31441e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005656809,"about_ca_system_score_gemma":0.00006399776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002673875,"about_ca_topic_score_gemma":0.000178775,"domain_scores_codex":[0.9976105,0.0002184415,0.0005617401,0.0005973904,0.0002585154,0.0007533868],"domain_scores_gemma":[0.999253,0.00007715278,0.0002191786,0.0001786516,0.0001618215,0.0001102059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001755549,0.00006366841,0.04808747,0.000005901605,0.004640601,0.00001422287,0.001503696,0.9140343,0.0001661276,0.01098151,0.00051393,0.01997099],"study_design_scores_gemma":[0.0001973867,0.000006703741,0.0006490379,0.00001647319,0.002954976,7.5069e-7,0.001766923,0.9905927,0.00001511087,0.003300556,0.00009559528,0.0004038079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4165333,0.0003607519,0.5813664,0.00005276385,0.0000599357,0.00005209737,0.000003873083,0.00007038313,0.001500567],"genre_scores_gemma":[0.9794014,0.00001267083,0.01507564,0.00007798993,0.005129993,0.000008831229,0.0001435333,0.00003938871,0.0001106041],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5662907,"threshold_uncertainty_score":0.9998768,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389831635","doi":"10.1007/s13278-023-01172-y","title":"Community detection in social networks by spectral embedding of typed graphs","year":2023,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Similarity (geometry); Embedding; Merge (version control); Data mining; Set (abstract data type); Cluster analysis; Graph; Community structure; Artificial intelligence; Theoretical computer science; Information retrieval; Machine learning; Mathematics; Image (mathematics)","retraction":null,"screen_n_in":null,"score":{"opus":0.0149298953611909,"gpt":0.2907132545255954,"spread":0.2757833591644045,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008977238,0.0001743285,0.0006004726,0.0003244054,0.0007720261,0.00004736329,0.0001473555,0.00009141282,0.00005879692],"category_scores_gemma":[0.000004297408,0.0001946047,0.0003805766,0.004565554,0.0001045856,0.00006907581,0.0001244292,0.0003656906,7.101658e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002554086,"about_ca_system_score_gemma":0.00001032264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001174806,"about_ca_topic_score_gemma":0.001092743,"domain_scores_codex":[0.9984472,0.0003456013,0.000429224,0.0002131141,0.0001496097,0.0004152874],"domain_scores_gemma":[0.9993867,0.0001407,0.0002605882,0.0001249855,0.00004547648,0.00004154774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007338316,0.000174576,0.8023324,0.00001926029,0.003726252,0.00000219027,0.006110017,0.02780327,0.0006499594,0.006408708,0.01098708,0.1417129],"study_design_scores_gemma":[0.001049064,0.0001104959,0.3485887,0.0000580481,0.00323233,2.355333e-7,0.01301619,0.5980772,0.000268617,0.03380401,0.0007762818,0.00101881],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978014,0.0000783001,0.02040466,0.00003596602,0.00003807718,0.00008082435,0.000008476784,0.00008058394,0.00125912],"genre_scores_gemma":[0.9989403,0.00001963684,0.0002171102,0.00001324678,0.0005320078,0.00001593667,0.0001735186,0.00001790524,0.00007033471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5702739,"threshold_uncertainty_score":0.793575,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400878910","doi":"10.1007/s13278-024-01290-1","title":"FakeWatch : a framework for detecting fake news to ensure credible elections","year":2024,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Bank of Canada; Toronto Metropolitan University; Vector Institute","funders":"","keywords":"Fake news; Computer science; Computer security; Internet privacy; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.03562317540701719,"gpt":0.3597862189072152,"spread":0.324163043500198,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0009058864,0.0001021982,0.0002315131,0.0002034988,0.002003674,0.0005547773,0.00008160052,0.0001519152,0.0001315531],"category_scores_gemma":[0.0004523111,0.0001007588,0.0002226341,0.003054024,0.00004263363,0.0001777493,0.00002467605,0.0001395098,0.00000775615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005626784,"about_ca_system_score_gemma":0.0001165529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005516484,"about_ca_topic_score_gemma":0.007976225,"domain_scores_codex":[0.99883,0.00007161451,0.0002360209,0.0002006971,0.000216271,0.0004454121],"domain_scores_gemma":[0.9992349,0.000383066,0.00006082464,0.00006460864,0.00008375025,0.0001728625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002483939,0.00001474787,0.002982409,0.00003578724,0.001151355,0.000001498654,0.3642519,0.00168428,0.00001978185,0.08557651,0.03705917,0.5071978],"study_design_scores_gemma":[0.0002246931,0.0001273149,0.005637241,0.000173584,0.001979173,9.385683e-7,0.2032023,0.01361419,0.00001764415,0.01995553,0.7543719,0.0006954858],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2899073,0.001154078,0.6635838,0.008769741,0.001240985,0.0006126615,0.00002415176,0.0004574464,0.03424992],"genre_scores_gemma":[0.9794269,0.000109302,0.01526516,0.0006664,0.002745589,0.0000156455,0.000009629924,0.0000129901,0.001748393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7173128,"threshold_uncertainty_score":0.9992956,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3025796795","doi":"10.1007/s13278-020-00656-5","title":"Neutrality may matter: sentiment analysis in reviews of Airbnb, Booking, and Couchsurfing in Brazil and USA","year":2020,"lang":"en","type":"preprint","venue":"Social Network Analysis and Mining","topic":"Sharing Economy and Platforms","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Sharing economy; Exploit; Business; Goods and services; Neutrality; File sharing; Sentiment analysis; Economy; Advertising; Internet privacy; Economics; Computer science; The Internet; World Wide Web; Computer security; Political science; Law","retraction":null,"screen_n_in":null,"score":{"opus":0.03117142763406631,"gpt":0.2755699528118128,"spread":0.2443985251777465,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001564488,0.0003139614,0.00163601,0.0007100516,0.0001598067,0.0003291542,0.0001437003,0.0002151688,0.0002105528],"category_scores_gemma":[0.00002427774,0.000315275,0.0003452876,0.001776614,0.00008218227,0.0002744093,0.0006764067,0.0003555666,0.000002791161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002843169,"about_ca_system_score_gemma":0.00001399958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003950281,"about_ca_topic_score_gemma":0.01001893,"domain_scores_codex":[0.9978917,0.000049304,0.0009314092,0.0006678807,0.0001337123,0.0003259417],"domain_scores_gemma":[0.9988496,0.00007607901,0.0008404479,0.0001759771,0.00003166702,0.00002624152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001938897,0.00001520397,0.9898108,0.0004668962,0.001185486,0.000005832802,0.0006975788,0.002178672,0.000001331259,0.0003012846,0.0004273769,0.004890139],"study_design_scores_gemma":[0.0002987167,0.000003144562,0.9667034,0.0001933054,0.004600945,1.626873e-7,0.0003330555,0.02319483,6.662563e-7,0.001163939,0.003132218,0.0003755926],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948168,0.002203438,0.0002202166,0.0006189639,0.0000780662,0.0002427934,0.000007433926,0.00001243306,0.001799885],"genre_scores_gemma":[0.997422,0.0008394108,0.0002859924,0.0008230194,0.0004286794,0.00001946196,0.0001162695,0.00001406491,0.00005114014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02310739,"threshold_uncertainty_score":0.9999299,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4394891674","doi":"10.1007/s13278-024-01242-9","title":"Uncertainty-aware graph neural network for semi-supervised diversified recommendation","year":2024,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Machine learning; Recommender system; Artificial intelligence; Generalization; Graph; Baseline (sea); Selection (genetic algorithm); Set (abstract data type); Supervised learning; Data mining; Artificial neural network; Theoretical computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.02814222950927422,"gpt":0.2769995083754443,"spread":0.2488572788661701,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007610152,0.0001759159,0.0003764548,0.0001625917,0.0007189232,0.0005095041,0.000255436,0.0001121957,0.00001381217],"category_scores_gemma":[0.000005628731,0.0001612799,0.0003696144,0.001761216,0.00002606009,0.0002937993,0.00015326,0.0001165691,7.385427e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003603517,"about_ca_system_score_gemma":0.00002280253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000127869,"about_ca_topic_score_gemma":0.0001837727,"domain_scores_codex":[0.998551,0.0001266455,0.000315228,0.0004810769,0.000124839,0.0004011925],"domain_scores_gemma":[0.9993658,0.0002447922,0.00009764881,0.0001535895,0.00006535599,0.00007282355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002296988,0.00002463701,0.009212766,0.0001012151,0.002493471,0.000009920145,0.005027662,0.01015075,0.00001141743,0.02856627,0.1372793,0.8070996],"study_design_scores_gemma":[0.0001815469,0.00006439838,0.0008369286,0.00004256159,0.000468732,0.000001572635,0.0004013402,0.9615688,0.000003835054,0.00607398,0.03006272,0.0002936384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006553807,0.0008093169,0.9884497,0.00213127,0.0008991298,0.0002390107,0.00001372542,0.0003861643,0.0005178581],"genre_scores_gemma":[0.9823086,0.0001195906,0.01525649,0.0004160248,0.001518051,0.00006190492,0.0001610311,0.0000152234,0.0001430963],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9757548,"threshold_uncertainty_score":0.6576803,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2051638022","doi":"10.1007/s13278-011-0041-9","title":"Exogenous control of DeGroot belief learning","year":2011,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"EcoMetrix","funders":"","keywords":"Control (management); Social learning; Computer science; Convergence (economics); Process (computing); Key (lock); Foundation (evidence); Artificial intelligence; Knowledge management; Economics; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.01313742969111655,"gpt":0.2347580831443666,"spread":0.22162065345325,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002478874,0.0001032714,0.0003666019,0.00005380081,0.0003908273,0.00002029726,0.00007531465,0.00004747332,0.0001696939],"category_scores_gemma":[0.00000355131,0.0001042011,0.0002325664,0.0004540746,0.00008371154,0.00004459565,0.00003273338,0.0001073984,0.000001263535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005427044,"about_ca_system_score_gemma":0.0000201296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007770322,"about_ca_topic_score_gemma":0.00005346741,"domain_scores_codex":[0.9991979,0.0000695306,0.0002487978,0.000158397,0.00009371775,0.0002316311],"domain_scores_gemma":[0.9995564,0.00004931571,0.0002110106,0.00006156213,0.00006935566,0.00005233875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001153492,0.00003706626,0.9396502,0.000003306232,0.001264,5.748577e-7,0.006271117,0.001398579,0.00001963339,0.02772436,0.00001884233,0.02360081],"study_design_scores_gemma":[0.00237904,0.0003616817,0.8865871,0.00006677085,0.006181322,4.453647e-7,0.0227668,0.05208299,0.0000670369,0.02551069,0.002656243,0.001339839],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9260114,0.0002342156,0.05905372,0.00001675705,0.00006905312,0.00006489292,0.00001073906,0.00001650004,0.0145227],"genre_scores_gemma":[0.9987905,0.00001139859,0.0006481733,0.00002503458,0.0003621283,0.000005324461,0.00001485651,0.000008785059,0.0001337818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0727791,"threshold_uncertainty_score":0.4249199,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4399708994","doi":"10.1007/s13278-024-01281-2","title":"Predicting properties of nodes via community-aware features","year":2024,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Narodowa Agencja Wymiany Akademickiej","keywords":"Node (physics); Computer science; Value (mathematics); Data mining; Artificial intelligence; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.01685068354156987,"gpt":0.2649264580893739,"spread":0.248075774547804,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005394753,0.0001743058,0.0005017106,0.0001790053,0.0006591202,0.0001340435,0.0001536642,0.00005482638,0.00006570766],"category_scores_gemma":[0.000003472314,0.0001510675,0.0004011536,0.001381035,0.000123298,0.00009631746,0.000160769,0.0003218834,5.922948e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001330088,"about_ca_system_score_gemma":0.00002186114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00155581,"about_ca_topic_score_gemma":0.0003622921,"domain_scores_codex":[0.9988203,0.0002165568,0.0003366455,0.000204686,0.0001610628,0.000260725],"domain_scores_gemma":[0.9994661,0.0001260946,0.000126833,0.0001661706,0.00007216602,0.00004261802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002766238,0.0001128503,0.7429978,0.0001812667,0.01268942,0.000002642493,0.01708105,0.003309663,0.001025449,0.008344424,0.002733473,0.2114943],"study_design_scores_gemma":[0.0008697347,0.0002854218,0.1723713,0.002222314,0.03577144,0.000004576824,0.05400512,0.6859611,0.004053753,0.03652894,0.005061457,0.002864938],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9642297,0.00265194,0.03015082,0.00008155272,0.00005691775,0.00009090573,0.00001214137,0.000149553,0.002576456],"genre_scores_gemma":[0.9980771,0.00001725686,0.0007410215,0.00001722789,0.0008673015,0.00001591747,0.00005544303,0.00001938655,0.0001893646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6826514,"threshold_uncertainty_score":0.6160355,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2583455222","doi":"10.1007/s13278-017-0421-x","title":"Selecting transfer entropy thresholds for influence network prediction","year":2017,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Transfer entropy; Computer science; Entropy (arrow of time); Data mining; Machine learning; Principle of maximum entropy; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01389321993858449,"gpt":0.2821688679491887,"spread":0.2682756480106042,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006682685,0.0002367832,0.0005906697,0.00007977935,0.003384476,0.0004189616,0.0002695134,0.00009048163,0.00006657643],"category_scores_gemma":[0.00001131545,0.0002423107,0.0005322724,0.0005070269,0.0001142727,0.0002362901,0.00009274064,0.0001709828,6.276214e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002274259,"about_ca_system_score_gemma":0.00002635058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002352441,"about_ca_topic_score_gemma":0.0002853706,"domain_scores_codex":[0.9983053,0.00006261758,0.0004164431,0.0004511804,0.0001731997,0.0005913263],"domain_scores_gemma":[0.9990792,0.000125912,0.0002582508,0.0003111847,0.0001367146,0.00008871197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003019811,0.00002194046,0.9364586,0.000005947014,0.002326704,3.994498e-7,0.0004937563,0.01554014,0.00005086388,0.01565547,0.00201359,0.02740243],"study_design_scores_gemma":[0.001752891,0.0001977163,0.6598727,0.0001412053,0.01380331,8.844474e-7,0.0008791271,0.2530405,0.0001301464,0.05225807,0.01653299,0.001390465],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7349281,0.0001558809,0.2624804,0.0001261114,0.0000955396,0.0002556948,0.00002131865,0.000090649,0.0018463],"genre_scores_gemma":[0.9907082,0.00002005972,0.00452384,0.00005108128,0.004344651,0.00008545807,0.00009070142,0.00002509489,0.0001508806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2765858,"threshold_uncertainty_score":0.997913,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2039584044","doi":"10.1007/s13278-013-0112-1","title":"Group disappearance in social networks with communities","year":2013,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Homophily; Node (physics); Group (periodic table); Computer science; Set (abstract data type); Social network (sociolinguistics); Flock; Network topology; Network formation; Quality (philosophy); Theoretical computer science; Data mining; Computer network; Mathematics; World Wide Web; Ecology; Social media; Engineering; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.009275801054004508,"gpt":0.2406136762712788,"spread":0.2313378752172743,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003078547,0.0002438885,0.0006612485,0.0001628958,0.0008134833,0.0001977208,0.0001903303,0.00007091027,0.0003277096],"category_scores_gemma":[5.973461e-7,0.0002223134,0.0002429876,0.001884895,0.0001934643,0.0001742076,0.000126966,0.0002900721,0.000002087562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000231239,"about_ca_system_score_gemma":0.00001020434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00327985,"about_ca_topic_score_gemma":0.003112911,"domain_scores_codex":[0.9984962,0.0001952188,0.000359846,0.0002522454,0.0001667016,0.0005297459],"domain_scores_gemma":[0.9994148,0.0001033308,0.0002040646,0.0001585542,0.00005966399,0.00005956135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001548753,0.00005811796,0.9389749,0.000003585752,0.001175841,8.952609e-7,0.002413042,0.005244073,0.00000197758,0.01069462,0.001732839,0.03968469],"study_design_scores_gemma":[0.0008542532,0.00007182025,0.8099387,0.0000755214,0.001736573,3.800139e-7,0.0151136,0.1603667,0.000001191576,0.009570067,0.001319179,0.0009519702],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9269388,0.0002805096,0.06711867,0.0001677819,0.00002139875,0.0001997791,0.000003122232,0.00007352699,0.005196426],"genre_scores_gemma":[0.9965461,0.00001760647,0.001789223,0.00009205933,0.001218303,0.0001008979,0.0001106487,0.00002376235,0.0001014383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1551227,"threshold_uncertainty_score":0.9065677,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2015036286","doi":"10.1007/s13278-013-0115-y","title":"A novel approach for modeling and managing spontaneous social communities over MANETs","year":2013,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"","keywords":"NetLogo; Computer science; Middleware (distributed applications); Identification (biology); Focus (optics); Mobile ad hoc network; Distributed computing; Order (exchange); Social network (sociolinguistics); Data science; World Wide Web; Computer network; Social media","retraction":null,"screen_n_in":null,"score":{"opus":0.03137474340898955,"gpt":0.2434539165718211,"spread":0.2120791731628315,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0004157374,0.0001974082,0.0004647857,0.0001158309,0.001321579,0.0004750606,0.000255812,0.0001241408,0.000008787373],"category_scores_gemma":[0.000001147719,0.0001960756,0.0001643967,0.0004409297,0.00008943097,0.0002347737,0.0002588286,0.0001476081,3.194065e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001788521,"about_ca_system_score_gemma":0.00001998172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003972724,"about_ca_topic_score_gemma":0.0001047108,"domain_scores_codex":[0.9986898,0.00005728833,0.0002995915,0.0003105152,0.0001755482,0.0004672841],"domain_scores_gemma":[0.9994055,0.0001462298,0.0001320178,0.0001482563,0.00007560147,0.00009236705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007200058,0.0001650771,0.004767974,0.0001377915,0.003230738,0.00003990679,0.04472836,0.05503283,0.000017067,0.04957784,0.003779985,0.8384504],"study_design_scores_gemma":[0.0002929342,0.00001871823,0.000382157,0.000009060676,0.0003481185,0.00001768538,0.002711643,0.9937387,3.216294e-8,0.002149842,0.00008968311,0.0002414749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07988019,0.0003383107,0.9177315,0.0001633533,0.00005934048,0.0001586686,0.000003574222,0.00005753328,0.001607519],"genre_scores_gemma":[0.920666,0.00005805209,0.07810062,0.0004050139,0.0005407973,0.00003490829,0.00004361767,0.00001370233,0.0001372881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9387058,"threshold_uncertainty_score":0.9999785,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}