{"meta":{"query_hash":"7547706352c2","filters":{"venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)"},"cohort_total":14,"direct_labels_cover":0,"predictions_cover":14,"exported":14,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/7547706352c2","api":"https://metacan.xera.ac/api/v1/cohort?venue=2016+IEEE%2FACM+International+Conference+on+Advances+in+Social+Networks+Analysis+and+Mining+%28ASONAM%29"},"results":[{"id":"W2549764709","doi":"10.1109/asonam.2016.7752208","title":"Streaming METIS partitioning","year":2016,"lang":"en","type":"preprint","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"Metis; Computer science; World Wide Web","score_opus":0.02902060170990805,"score_gpt":0.31877364606897796,"score_spread":0.2897530443590699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2549764709","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045758422,0.00079796836,0.9344717,0.0004327848,0.00023253418,0.0005949469,0.0025306316,0.0057781455,0.009402782],"genre_scores_gemma":[0.21062057,0.00034043108,0.77375734,0.0001923588,0.00010173504,0.0004977113,0.0076936255,0.0010085206,0.005787665],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991906,0.00014508689,0.000057828485,0.00030994433,0.00020424834,0.000092350274],"domain_scores_gemma":[0.99848336,0.00047431022,0.00011427039,0.00053362164,0.00027920806,0.000115202325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052303757,0.0011725627,0.0009623652,0.0012971931,0.0009190987,0.0016653808,0.0015768786,0.0008070055,0.006091124],"category_scores_gemma":[0.003081652,0.00040632876,0.0010625558,0.0016155035,0.00040219547,0.0020327265,0.0014273613,0.0008396279,0.002087108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008727828,0.00038986816,0.0037473128,0.00089170755,0.00021688278,0.00046817918,0.00054303004,0.20723583,0.041727245,0.033079896,0.04592704,0.66490024],"study_design_scores_gemma":[0.00010530581,0.00021131146,0.0017111332,0.000044290835,0.000049760307,0.000479766,0.000457873,0.9127394,0.018426485,0.03653795,0.029205969,0.000030800027],"about_ca_topic_score_codex":0.003295876,"about_ca_topic_score_gemma":0.007362804,"teacher_disagreement_score":0.006091124,"about_ca_system_score_codex":0.000822118,"about_ca_system_score_gemma":0.0013007263,"threshold_uncertainty_score":0.020376801},"labels":[],"label_agreement":null},{"id":"W4230379130","doi":"10.1109/asonam.2016.7752404","title":"Observations on the role of influence in the difficulty of social network control","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Controllability; Heuristics; Control (management); Selection (genetic algorithm); Computer science; Heuristic; Set (abstract data type); Controller (irrigation); Network controllability; Work (physics); Control network; Artificial intelligence; Engineering; Mathematics; Statistics","score_opus":0.019237722273358872,"score_gpt":0.29775999846498713,"score_spread":0.2785222761916283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230379130","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45049205,0.0014870326,0.50775665,0.00342899,0.00012341408,0.00018133907,0.0002735742,0.0002768984,0.035979975],"genre_scores_gemma":[0.9851393,0.00032078105,0.013387316,0.000058941307,0.000080182646,0.00005529936,0.00007847924,0.000028503757,0.0008511699],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978205,0.0006936835,0.00013101572,0.00062548416,0.00047885603,0.00025052996],"domain_scores_gemma":[0.8963415,0.09205875,0.004250572,0.0038724418,0.0021447502,0.0013320296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042873872,0.0009659832,0.0012297694,0.0015687518,0.0010579253,0.0018189065,0.0015031055,0.0016379203,0.005421901],"category_scores_gemma":[0.055019256,0.0005734753,0.0010649312,0.00077042205,0.0037110096,0.0051162676,0.001717724,0.0029815983,0.0002875696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00074887753,0.0005364288,0.038309697,0.0010550357,0.0003657907,0.0009465828,0.0045374013,0.4873779,0.014361313,0.3795892,0.0037499664,0.06842177],"study_design_scores_gemma":[0.00008428924,0.00025437327,0.016626628,0.000069742826,0.000052009338,0.00039944047,0.00054121506,0.62626696,0.0041086744,0.34922266,0.0022650864,0.000108933986],"about_ca_topic_score_codex":0.0029667642,"about_ca_topic_score_gemma":0.0020192147,"teacher_disagreement_score":0.005421901,"about_ca_system_score_codex":0.0011441321,"about_ca_system_score_gemma":0.00034327823,"threshold_uncertainty_score":0.022674143},"labels":[],"label_agreement":null},{"id":"W4230603371","doi":"10.1109/asonam.2016.7752356","title":"Spectral graph-based semi-supervised learning for imbalanced classes","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Artificial intelligence; Graph; Machine learning; Semi-supervised learning; Theoretical computer science","score_opus":0.03140565970496059,"score_gpt":0.3221481992779155,"score_spread":0.29074253957295493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230603371","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021644162,0.00020888395,0.9753032,0.0002829425,0.00005383639,0.00009643523,0.00014583033,0.0015741087,0.0006906344],"genre_scores_gemma":[0.49018607,0.00023841926,0.50441754,0.0004222189,0.00018060868,0.00044286516,0.0016155571,0.00038909895,0.002107711],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9964644,0.0013851995,0.00021919003,0.0007765487,0.0009779418,0.00017666111],"domain_scores_gemma":[0.9834065,0.0092967115,0.0017419511,0.0028756727,0.0022143952,0.000464842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058133393,0.0013635027,0.0021771642,0.0032979427,0.0013102383,0.001496295,0.0036609247,0.0019728267,0.0015561463],"category_scores_gemma":[0.018686667,0.00061746157,0.0010903805,0.0024507002,0.0021228357,0.0037473836,0.0026388692,0.0025758862,0.0010481082],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004965506,0.0004243101,0.004706475,0.00024267659,0.00021257397,0.00017398072,0.0004497651,0.51479524,0.004145843,0.02049989,0.009317901,0.44453478],"study_design_scores_gemma":[0.00000841245,0.000016527658,0.00014333628,0.000005579609,0.0000046882387,0.000019700798,0.000024043518,0.98517543,0.0006114751,0.0136863375,0.00029853024,0.000006036144],"about_ca_topic_score_codex":0.0026401544,"about_ca_topic_score_gemma":0.0041066906,"teacher_disagreement_score":0.0058133393,"about_ca_system_score_codex":0.0015618957,"about_ca_system_score_gemma":0.0015968136,"threshold_uncertainty_score":0.030744255},"labels":[],"label_agreement":null},{"id":"W4231557727","doi":"10.1109/asonam.2016.7752293","title":"Mining hidden constrained streams in practice: Informed search in dynamic filter spaces","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Data stream mining; Set (abstract data type); Filter (signal processing); Data stream; Data mining; Dynamic data; Space (punctuation); Tracking (education); Selection (genetic algorithm); Data set; Data science; Artificial intelligence; Database","score_opus":0.028155809476214357,"score_gpt":0.3568444888092165,"score_spread":0.3286886793330021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231557727","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031401638,0.0007276833,0.9657377,0.00077108946,0.000030589603,0.00009194046,0.00022281773,0.00033019859,0.00068645197],"genre_scores_gemma":[0.55736876,0.0010948059,0.43655357,0.0005691007,0.00032325694,0.00042579352,0.0015508537,0.0001702613,0.0019436183],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996727,0.0014036583,0.00026834587,0.00078007096,0.00055197615,0.00026888278],"domain_scores_gemma":[0.96458215,0.031171972,0.0015801019,0.0012491377,0.00097328326,0.0004433158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007846035,0.0016619801,0.0035755492,0.0037287837,0.0012611203,0.003871301,0.0034669966,0.0035611093,0.001889794],"category_scores_gemma":[0.032396518,0.00173375,0.0014614334,0.0040109884,0.0021054978,0.0075438633,0.0031884431,0.0025967478,0.00045410855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027955335,0.00023487362,0.006089393,0.00028660588,0.0002535647,0.00027363462,0.0004209731,0.8830724,0.0006251516,0.04170511,0.0021026917,0.06465605],"study_design_scores_gemma":[0.000017108143,0.00002200671,0.0001269969,0.0000114871455,0.000009920811,0.00001613801,0.000039393017,0.97649604,0.00012700103,0.02285904,0.0002681516,0.0000066988146],"about_ca_topic_score_codex":0.0064749676,"about_ca_topic_score_gemma":0.0068604797,"teacher_disagreement_score":0.007846035,"about_ca_system_score_codex":0.0017531269,"about_ca_system_score_gemma":0.0023940133,"threshold_uncertainty_score":0.04149431},"labels":[],"label_agreement":null},{"id":"W4233132785","doi":"10.1109/asonam.2016.7752350","title":"Mining ‘following’ patterns from big sparse social networks","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Big data; Data science; Data mining","score_opus":0.03686138174885396,"score_gpt":0.31198912031532094,"score_spread":0.275127738566467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233132785","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55947,0.0012944622,0.42213532,0.0019285704,0.00010370152,0.00047308052,0.007557679,0.0013152522,0.005721876],"genre_scores_gemma":[0.8516133,0.00055714045,0.13703622,0.00021914922,0.00010602034,0.0002880143,0.008802792,0.000048304417,0.001329182],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851936,0.000351752,0.00013410658,0.00035041844,0.000518385,0.00012591446],"domain_scores_gemma":[0.99277765,0.0036407518,0.0013805312,0.0011350029,0.0008359518,0.00023019346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009205512,0.00079904514,0.000918783,0.004566441,0.0008598538,0.00097224093,0.0016315721,0.0013702777,0.0009748645],"category_scores_gemma":[0.010281394,0.00044005323,0.00082882866,0.00420847,0.00072220876,0.0026637653,0.0013705773,0.0008371654,0.00052704796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001079574,0.00088924303,0.22945149,0.0012788753,0.00078053045,0.0044790045,0.0034007903,0.19929023,0.019465644,0.037487917,0.021369854,0.48102692],"study_design_scores_gemma":[0.000034002882,0.0001569551,0.025612652,0.00008597576,0.00010913024,0.001214139,0.0012828211,0.8963936,0.0051480653,0.061101764,0.008826043,0.000034909805],"about_ca_topic_score_codex":0.00387494,"about_ca_topic_score_gemma":0.0074091596,"teacher_disagreement_score":0.004566441,"about_ca_system_score_codex":0.00052547065,"about_ca_system_score_gemma":0.00049469847,"threshold_uncertainty_score":0.007704735},"labels":[],"label_agreement":null},{"id":"W4234384890","doi":"10.1109/asonam.2016.7752349","title":"Big data mining of social networks for friend recommendation","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Big data; Computer science; Data science; World Wide Web; Data mining","score_opus":0.07381743422395404,"score_gpt":0.3655441414783744,"score_spread":0.29172670725442035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234384890","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16300017,0.002494818,0.8057613,0.002938944,0.0002653582,0.00085721264,0.009356928,0.00448178,0.01084356],"genre_scores_gemma":[0.6792642,0.0010196168,0.30747342,0.0002531959,0.00017311885,0.00043888405,0.0083888,0.0001237927,0.0028650018],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987031,0.0003278552,0.000088691886,0.00036118264,0.00041100846,0.00010811464],"domain_scores_gemma":[0.9969292,0.0013114293,0.00037538697,0.00057469186,0.00061907555,0.00019014943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011334178,0.001242354,0.0009717946,0.005281021,0.0015130076,0.0014856282,0.0018677172,0.0010919439,0.0018661087],"category_scores_gemma":[0.009236263,0.0004727082,0.0013666059,0.004473177,0.0004986454,0.0027156104,0.0011090877,0.0010363676,0.0012587508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006895246,0.001349243,0.092479065,0.0011844464,0.0011596655,0.0014133829,0.001976434,0.21299164,0.008968212,0.04059479,0.046506163,0.5906874],"study_design_scores_gemma":[0.000026804748,0.00007781075,0.0071596885,0.000065986824,0.00010451346,0.0003393436,0.0008186791,0.92385125,0.0039075813,0.05279533,0.01082283,0.000030145784],"about_ca_topic_score_codex":0.010223071,"about_ca_topic_score_gemma":0.01963707,"teacher_disagreement_score":0.010223071,"about_ca_system_score_codex":0.001053784,"about_ca_system_score_gemma":0.001065963,"threshold_uncertainty_score":0.020327091},"labels":[],"label_agreement":null},{"id":"W4234995558","doi":"10.1109/asonam.2016.7752337","title":"Retweet prediction considering user's difference as an author and retweeter","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Field (mathematics); Social network (sociolinguistics); Social network analysis; Data science; Significant difference; Social influence; Social media; World Wide Web; Psychology; Mathematics; Statistics","score_opus":0.03138906469607681,"score_gpt":0.3349104635776121,"score_spread":0.3035213988815353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234995558","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8451159,0.0012250285,0.14235651,0.000778324,0.00035073014,0.0003335637,0.002243331,0.0012121061,0.0063844966],"genre_scores_gemma":[0.9754877,0.00037130367,0.01875486,0.00006333433,0.00013198282,0.000086395055,0.0013376619,0.0000450026,0.0037216248],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871874,0.00022722351,0.00012482231,0.00039150126,0.0003952277,0.0001424688],"domain_scores_gemma":[0.9916773,0.0040598065,0.0012195981,0.00071257964,0.001989866,0.00034085472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015951252,0.0013045477,0.0008704856,0.0037143396,0.0008007972,0.0013741571,0.0010781401,0.0011118954,0.0012043151],"category_scores_gemma":[0.009118953,0.0003293762,0.0008123542,0.0023337866,0.0003720912,0.003641126,0.0007332325,0.0013554759,0.0011306524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010579315,0.0010050554,0.57147324,0.00044498246,0.0005267291,0.001587156,0.0016065856,0.06890523,0.013109741,0.004827163,0.0094697345,0.32598644],"study_design_scores_gemma":[0.000016329119,0.00028812274,0.06461132,0.000038326343,0.00023570431,0.0006003631,0.0004795474,0.9194163,0.007119151,0.0042097312,0.0029055304,0.000079648475],"about_ca_topic_score_codex":0.00825264,"about_ca_topic_score_gemma":0.012449641,"teacher_disagreement_score":0.00825264,"about_ca_system_score_codex":0.0005203171,"about_ca_system_score_gemma":0.00047621617,"threshold_uncertainty_score":0.016409218},"labels":[],"label_agreement":null},{"id":"W4235014373","doi":"10.1109/asonam.2016.7752343","title":"Understanding alliance and opposition among violent groups","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Opposition (politics); Alliance; Situational ethics; Political science; Political economy; Computer science; Social psychology; Sociology; Psychology; Politics","score_opus":0.05710934282861807,"score_gpt":0.3243031271787189,"score_spread":0.2671937843501008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235014373","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7959024,0.00065825577,0.15569581,0.0025487153,0.000056654488,0.00008427739,0.00021618717,0.00009932652,0.044738356],"genre_scores_gemma":[0.9859272,0.00019303604,0.012525682,0.000055223165,0.0000150631895,0.00004271196,0.00010957393,0.00001210463,0.0011194269],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9988624,0.0006601771,0.000041783725,0.0001783802,0.00016314354,0.0000941697],"domain_scores_gemma":[0.9947937,0.0032099069,0.0010699752,0.00032965868,0.00033779247,0.0002589456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018786964,0.0002707511,0.00028454425,0.0020281582,0.0012117928,0.0026461163,0.0007019132,0.0008622881,0.0035777143],"category_scores_gemma":[0.012354397,0.00022932516,0.00033056436,0.0015549843,0.0023457399,0.006541704,0.0031923223,0.0011695548,0.00030639523],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015846142,0.00017093991,0.08119117,0.0002758124,0.000110487264,0.0007669168,0.051675387,0.02230778,0.0030822046,0.74035245,0.003089836,0.096818425],"study_design_scores_gemma":[0.000026149743,0.0000750179,0.041567713,0.00014527449,0.00006749187,0.00046815106,0.04485562,0.14638393,0.0012170146,0.741416,0.023728611,0.000049038725],"about_ca_topic_score_codex":0.0034439496,"about_ca_topic_score_gemma":0.0035800578,"teacher_disagreement_score":0.0035777143,"about_ca_system_score_codex":0.0007876892,"about_ca_system_score_gemma":0.00040652117,"threshold_uncertainty_score":0.011968613},"labels":[],"label_agreement":null},{"id":"W4237060534","doi":"10.1109/asonam.2016.7752399","title":"Stream clustering of tweets","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Computer science; Partition (number theory); Cluster analysis; Social media; Process (computing); Data mining; Plan (archaeology); Cluster (spacecraft); Information retrieval; Data science; Machine learning; World Wide Web","score_opus":0.025249568505512375,"score_gpt":0.3295063109840421,"score_spread":0.30425674247852974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237060534","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036822066,0.0005257943,0.95326954,0.0004149872,0.00038486795,0.0006363987,0.002409137,0.0018345691,0.0037025718],"genre_scores_gemma":[0.29264626,0.0009158418,0.6858983,0.00018330046,0.00069822365,0.00091355026,0.00871862,0.0005152369,0.009510623],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998727,0.0002308957,0.0001023854,0.00039005792,0.00040840078,0.00014125157],"domain_scores_gemma":[0.99729794,0.0007874283,0.0003027148,0.00035108396,0.0011436796,0.00011718138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011725549,0.0013065776,0.0010657203,0.0054969564,0.0014148443,0.0021835172,0.00149688,0.0009257871,0.0025088906],"category_scores_gemma":[0.005557275,0.0004816715,0.0013299893,0.0044108965,0.0005032111,0.001837696,0.0010721387,0.0009867332,0.002082191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014355312,0.00052248995,0.022237279,0.0009424325,0.0004963522,0.00063885684,0.0018320312,0.1916198,0.034229565,0.040191196,0.033314127,0.67254037],"study_design_scores_gemma":[0.000056404264,0.0001404926,0.00574959,0.00007333345,0.00010684934,0.0002546716,0.0007835704,0.905982,0.017359065,0.036047734,0.033380657,0.00006559171],"about_ca_topic_score_codex":0.0054614786,"about_ca_topic_score_gemma":0.0063810246,"teacher_disagreement_score":0.0054969564,"about_ca_system_score_codex":0.0012989461,"about_ca_system_score_gemma":0.0011784335,"threshold_uncertainty_score":0.01085937},"labels":[],"label_agreement":null},{"id":"W4239270184","doi":"10.1109/asonam.2016.7752351","title":"Frequent and non-frequent pattern detection in big data streams: An experimental simulation in 1 trillion data points","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Big data; String (physics); Suffix; Data mining; Data stream mining; Point (geometry); Data structure; Data modeling; Database; Operating system","score_opus":0.08813651274119436,"score_gpt":0.365066864245738,"score_spread":0.2769303515045436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239270184","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.979575,0.00026690602,0.017142827,0.00032964908,0.00011473279,0.00013218263,0.0007577303,0.00068853144,0.000992362],"genre_scores_gemma":[0.96820503,0.00016606905,0.029013176,0.00007961653,0.00002844593,0.0001397627,0.0016391991,0.000040882485,0.0006878039],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844754,0.00040802805,0.00013998557,0.00026324883,0.0005073298,0.000233956],"domain_scores_gemma":[0.9870935,0.009103874,0.0004598091,0.0012015228,0.0015819994,0.00055929524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021908497,0.0006189452,0.00080661115,0.0010057503,0.00059025147,0.00074713497,0.0012125352,0.0010195756,0.0013836768],"category_scores_gemma":[0.011652034,0.0002831055,0.000694452,0.0014520849,0.0007580554,0.0013386908,0.0007729488,0.0012595814,0.000325456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0060923444,0.006237814,0.07239095,0.00089729956,0.00050667144,0.0019379286,0.00102379,0.73052394,0.029023279,0.007109474,0.011948721,0.13230771],"study_design_scores_gemma":[0.000121162404,0.0006724235,0.006225909,0.00001437593,0.000029282739,0.00017424738,0.00021905013,0.98130804,0.008784307,0.0017929112,0.00063890155,0.00001939312],"about_ca_topic_score_codex":0.0048022536,"about_ca_topic_score_gemma":0.0036416415,"teacher_disagreement_score":0.0048022536,"about_ca_system_score_codex":0.000585261,"about_ca_system_score_gemma":0.0008081075,"threshold_uncertainty_score":0.011586428},"labels":[],"label_agreement":null},{"id":"W4242981398","doi":"10.1109/asonam.2016.7752211","title":"Tradeoffs between density and size in extracting dense subgraphs: A unified framework","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Maximization; Range (aeronautics); Quadratic equation; Generalization; Theoretical computer science; Mathematical optimization; Mathematics","score_opus":0.0412797631814928,"score_gpt":0.34760454320269846,"score_spread":0.30632478002120567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242981398","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00922734,0.0008382437,0.98784196,0.0003659509,0.000015011756,0.000091019865,0.000068426714,0.0003167781,0.0012351645],"genre_scores_gemma":[0.1865298,0.0014864217,0.8092846,0.00025319448,0.00013778002,0.00044104728,0.00035762787,0.0003547453,0.0011547789],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9917454,0.0039050675,0.0004088229,0.0014832822,0.0019546156,0.00050282],"domain_scores_gemma":[0.97592443,0.016854478,0.0013317293,0.0032212995,0.0020306623,0.00063734275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012753765,0.00209577,0.0027925156,0.0052755857,0.0016997011,0.003959973,0.004303632,0.0028221002,0.001985046],"category_scores_gemma":[0.042924885,0.0018301264,0.0020331957,0.004980296,0.0035232643,0.014321796,0.006277513,0.0034805918,0.00052031415],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022947472,0.00037055268,0.0064199474,0.000682822,0.00024411506,0.00026497492,0.00081083947,0.54015183,0.009098465,0.17495558,0.005713184,0.2610582],"study_design_scores_gemma":[0.000024185481,0.00007791259,0.0009001701,0.000061144034,0.000074365424,0.00020541059,0.00012225058,0.9279091,0.0018598848,0.06677328,0.001953759,0.000038510945],"about_ca_topic_score_codex":0.0037524926,"about_ca_topic_score_gemma":0.0075861714,"teacher_disagreement_score":0.012753765,"about_ca_system_score_codex":0.0027472484,"about_ca_system_score_gemma":0.0026257369,"threshold_uncertainty_score":0.06744921},"labels":[],"label_agreement":null},{"id":"W4247420201","doi":"10.1109/asonam.2016.7752277","title":"Dynamics of large scale networks following a merger","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Computer science; Server; Network dynamics; Dynamics (music); Network topology; Network structure; Distributed computing; Computer network; Physics; Mathematics","score_opus":0.014043518471828066,"score_gpt":0.3189464344121986,"score_spread":0.30490291594037056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247420201","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98292625,0.00032297394,0.011086444,0.00095584703,0.000033770943,0.000032408792,0.0002461599,0.0001100021,0.004286247],"genre_scores_gemma":[0.99673444,0.00010505256,0.0020404977,0.00004800066,0.000013878799,0.000025568852,0.00024285809,0.000018197152,0.00077149755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995571,0.00014428374,0.00001397948,0.000102930724,0.00009364418,0.00008813927],"domain_scores_gemma":[0.9966857,0.0014478866,0.00067607994,0.00023526355,0.0003180203,0.00063705124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008630941,0.00028719095,0.0003821507,0.0013667679,0.0011321639,0.001348849,0.0007996526,0.00086759863,0.002329925],"category_scores_gemma":[0.011144329,0.00035767598,0.00033212706,0.00096290355,0.0012933088,0.0031686046,0.0017224401,0.0010287925,0.00024842212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013895303,0.00075434207,0.198299,0.00033206944,0.0004902864,0.0056849355,0.014617503,0.46823725,0.04759348,0.177937,0.019177627,0.06548695],"study_design_scores_gemma":[0.00009046074,0.0002944743,0.09843273,0.000063464635,0.00008967463,0.0008441728,0.0052731023,0.8166846,0.0035356316,0.06312384,0.011450543,0.00011720419],"about_ca_topic_score_codex":0.008707342,"about_ca_topic_score_gemma":0.007150327,"teacher_disagreement_score":0.008707342,"about_ca_system_score_codex":0.001224425,"about_ca_system_score_gemma":0.00039660695,"threshold_uncertainty_score":0.017313302},"labels":[],"label_agreement":null},{"id":"W4247473813","doi":"10.1109/asonam.2016.7752406","title":"Stability of certainty and opinion in influence networks","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Certainty; Stability (learning theory); Computer science; Mathematics; Machine learning","score_opus":0.023252479489990818,"score_gpt":0.32577372762214,"score_spread":0.3025212481321492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247473813","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060510453,0.0006677079,0.9252495,0.0012868088,0.00006604455,0.00011415458,0.00026513956,0.0005785396,0.011261718],"genre_scores_gemma":[0.8964717,0.0010123276,0.093533345,0.0002547206,0.00025935317,0.0003424763,0.0004421073,0.00021820489,0.007465817],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.994989,0.0017614049,0.0002090635,0.0011349639,0.0013344949,0.0005709571],"domain_scores_gemma":[0.96845734,0.023921646,0.0025821757,0.002113207,0.0019020685,0.0010236504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004932948,0.0011822308,0.0015809106,0.0016775524,0.0020036164,0.0043365043,0.0025482108,0.0020936748,0.008128345],"category_scores_gemma":[0.049878284,0.00081606087,0.0017031651,0.0014279173,0.0035166496,0.00927425,0.0038933835,0.0029608742,0.0011605329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042783475,0.000050155155,0.0019902359,0.00017774545,0.0000812658,0.00016131347,0.0009913457,0.24994157,0.0025819533,0.7075407,0.0022474714,0.033808384],"study_design_scores_gemma":[0.000038324168,0.000053915133,0.0003176731,0.000022632228,0.00002406403,0.000067091496,0.00012035549,0.60845876,0.0012799101,0.38685933,0.0027274908,0.000030455023],"about_ca_topic_score_codex":0.005324192,"about_ca_topic_score_gemma":0.0025387362,"teacher_disagreement_score":0.008128345,"about_ca_system_score_codex":0.0039163134,"about_ca_system_score_gemma":0.0015252206,"threshold_uncertainty_score":0.028414965},"labels":[],"label_agreement":null},{"id":"W4253544295","doi":"10.1109/asonam.2016.7752361","title":"An experimental evaluation of giraph and GraphChi","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"PageRank; Computer science; Implementation; Computation; Graph; Parallel computing; Theoretical computer science; Computer cluster; Focus (optics); Distributed computing; Operating system; Algorithm; Programming language","score_opus":0.036848360576902904,"score_gpt":0.350615048449353,"score_spread":0.3137666878724501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253544295","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5911013,0.019439043,0.09185303,0.0053373463,0.006793496,0.0031236869,0.03478106,0.18746004,0.06011104],"genre_scores_gemma":[0.63832086,0.0032507386,0.25918657,0.0021484136,0.0007136446,0.0016085266,0.07805502,0.007748478,0.008967795],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.987463,0.004607412,0.000852805,0.0026943993,0.0035295642,0.00085276196],"domain_scores_gemma":[0.97303265,0.012057734,0.0007362869,0.007517966,0.0053810473,0.0012741857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008280262,0.0032635848,0.0021373508,0.004591688,0.002616954,0.0030305237,0.0052129696,0.0029601664,0.0064668283],"category_scores_gemma":[0.03757396,0.000896173,0.0013336323,0.0061209765,0.001964335,0.0072010453,0.0029364873,0.0030819497,0.0052763135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009531014,0.0040583233,0.01867218,0.0067487042,0.0020065426,0.00040979637,0.00091675564,0.14395842,0.013814102,0.01887036,0.38500148,0.39601222],"study_design_scores_gemma":[0.0028879633,0.006024755,0.02169623,0.0005206639,0.0006536106,0.0015167298,0.0018883464,0.76925343,0.039126646,0.032791547,0.123242445,0.00039762165],"about_ca_topic_score_codex":0.01037465,"about_ca_topic_score_gemma":0.012680987,"teacher_disagreement_score":0.01037465,"about_ca_system_score_codex":0.002453552,"about_ca_system_score_gemma":0.0026058871,"threshold_uncertainty_score":0.043790758},"labels":[],"label_agreement":null}]}