{"meta":{"query_hash":"36750f61a174","filters":{"venue":"The Review of Socionetwork Strategies"},"cohort_total":6,"direct_labels_cover":0,"predictions_cover":6,"exported":6,"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/36750f61a174","api":"https://metacan.xera.ac/api/v1/cohort?venue=The+Review+of+Socionetwork+Strategies"},"results":[{"id":"W4210931461","doi":"10.1007/s12626-022-00103-1","title":"Legal Information Retrieval and Entailment Based on BM25, Transformer and Semantic Thesaurus Methods","year":2022,"lang":"en","type":"article","venue":"The Review of Socionetwork Strategies","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Textual entailment; Natural language processing; Logical consequence; Information retrieval; Artificial intelligence; Thesaurus; Information extraction; Question answering; Natural language; Task (project management); Semantic computing; Semantic Web","score_opus":0.03401550290011908,"score_gpt":0.38594936615372927,"score_spread":0.3519338632536102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210931461","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":[0.027893862,0.01761047,0.9141791,0.00109764,0.0007527113,0.0024388998,0.004177035,0.014508358,0.017341873],"genre_scores_gemma":[0.10950744,0.0032281815,0.8711721,0.00036851698,0.0004337502,0.0015196601,0.007864256,0.0006881262,0.0052179573],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99317074,0.0021223116,0.0011151277,0.0012232767,0.0020621358,0.00030647844],"domain_scores_gemma":[0.99661154,0.0015149394,0.00025910823,0.0004579505,0.001049961,0.00010641632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00840282,0.0033054717,0.0025766005,0.024449907,0.0019094078,0.0036156815,0.0038161378,0.00280684,0.008065275],"category_scores_gemma":[0.01643465,0.00086003524,0.0031110826,0.012201033,0.0011607574,0.0039588693,0.0020127103,0.0019503707,0.004858568],"study_design_candidate":"bench_or_experimental","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":[0.00027305522,0.00024986634,0.000710471,0.0011396009,0.0005694038,0.0001749583,0.00022709882,0.014520802,0.006501184,0.006849019,0.024517482,0.944267],"study_design_scores_gemma":[0.00046787382,0.00067258376,0.008975941,0.0003870655,0.0014189304,0.0009015227,0.00057214015,0.8340122,0.03856288,0.05374144,0.059967045,0.00032041257],"about_ca_topic_score_codex":0.017704502,"about_ca_topic_score_gemma":0.020960165,"teacher_disagreement_score":0.024449907,"about_ca_system_score_codex":0.0029732424,"about_ca_system_score_gemma":0.0030716483,"threshold_uncertainty_score":0.0444389},"labels":[],"label_agreement":null},{"id":"W4213191780","doi":"10.1007/s12626-022-00105-z","title":"Overview and Discussion of the Competition on Legal Information Extraction/Entailment (COLIEE) 2021","year":2022,"lang":"en","type":"article","venue":"The Review of Socionetwork Strategies","topic":"Topic Modeling","field":"Computer Science","cited_by":80,"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 Alberta","funders":"Hokkaido University; Shizuoka University; University of Alberta; National Institute of Informatics; Alberta Machine Intelligence Institute","keywords":"Task (project management); Statute; Computer science; Logical consequence; Component (thermodynamics); Competition (biology); Natural language processing; Information retrieval; Law; Artificial intelligence; Political science","score_opus":0.020410539368644436,"score_gpt":0.28133437493635527,"score_spread":0.2609238355677108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213191780","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":[0.06291305,0.09021676,0.28323188,0.12089659,0.056547917,0.00946552,0.09895205,0.04033627,0.23743999],"genre_scores_gemma":[0.102721244,0.01731185,0.29382637,0.02121551,0.00951148,0.00655691,0.35854,0.021954654,0.1683621],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9531818,0.019192448,0.0028342656,0.004494868,0.016759919,0.0035367387],"domain_scores_gemma":[0.9140526,0.028346084,0.0015578545,0.007124057,0.039504204,0.009415219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.067475215,0.0032466687,0.0034431953,0.012307995,0.0058367695,0.011581243,0.0062766173,0.004500407,0.03971196],"category_scores_gemma":[0.068088435,0.0011075283,0.0027728213,0.012420965,0.002067359,0.010028316,0.009134989,0.00476075,0.026311887],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038129714,0.0004255842,0.00089667336,0.0012170629,0.00009700645,0.00008134999,0.0004456859,0.001738109,0.002032159,0.0054452936,0.8278228,0.15941714],"study_design_scores_gemma":[0.00017929499,0.0003106623,0.00396632,0.00051852234,0.00005700268,0.00019557307,0.0006071583,0.009491152,0.0042914697,0.006774875,0.973464,0.0001439378],"about_ca_topic_score_codex":0.028812494,"about_ca_topic_score_gemma":0.052695286,"teacher_disagreement_score":0.067475215,"about_ca_system_score_codex":0.008516013,"about_ca_system_score_gemma":0.011698908,"threshold_uncertainty_score":0.3568473},"labels":[],"label_agreement":null},{"id":"W4390745240","doi":"10.1007/s12626-023-00153-z","title":"Legal Information Retrieval and Entailment Using Transformer-based Approaches","year":2024,"lang":"en","type":"article","venue":"The Review of Socionetwork Strategies","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":15,"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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; University of Alberta; Alberta Machine Intelligence Institute","keywords":"Computer science; Transformer; Textual entailment; Information retrieval; Logical consequence; Natural language processing; Artificial intelligence; Physics; Voltage; Quantum mechanics","score_opus":0.09925702547852286,"score_gpt":0.36733460609135166,"score_spread":0.2680775806128288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390745240","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":[0.01702856,0.0031716507,0.9695123,0.0010581751,0.000107844186,0.0003085461,0.0009631432,0.0034292496,0.0044204798],"genre_scores_gemma":[0.42020038,0.0031810147,0.5612227,0.0007154052,0.00038767015,0.00031291554,0.0075848554,0.0004572748,0.005937854],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996819,0.0011782638,0.0003477813,0.0006816244,0.0008079998,0.00016526993],"domain_scores_gemma":[0.9954626,0.0028373639,0.00024026808,0.00063901057,0.00072121515,0.00009944414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003782391,0.0010615324,0.0014255403,0.0076187695,0.00090800284,0.0024069713,0.002831665,0.0011843764,0.0050416263],"category_scores_gemma":[0.010055406,0.0005409778,0.0020817472,0.0043381555,0.0011431833,0.007344651,0.0023786442,0.002117496,0.002228642],"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":[0.0003097029,0.0002827254,0.001748829,0.0008029808,0.00025816343,0.00018040888,0.00040332595,0.046680003,0.006047813,0.04618801,0.01749946,0.8795985],"study_design_scores_gemma":[0.00007039368,0.00012821617,0.0011504152,0.00007298588,0.00016344125,0.00028289983,0.00021083,0.85809886,0.007955321,0.12047027,0.011350503,0.0000458984],"about_ca_topic_score_codex":0.009330667,"about_ca_topic_score_gemma":0.011868585,"teacher_disagreement_score":0.009330667,"about_ca_system_score_codex":0.0022893427,"about_ca_system_score_gemma":0.0019240013,"threshold_uncertainty_score":0.020003438},"labels":[],"label_agreement":null},{"id":"W4390822940","doi":"10.1007/s12626-023-00152-0","title":"Overview and Discussion of the Competition on Legal Information, Extraction/Entailment (COLIEE) 2023","year":2024,"lang":"en","type":"article","venue":"The Review of Socionetwork Strategies","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":12,"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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Informatics; Shizuoka University; Alberta Innovates; Alberta Machine Intelligence Institute; Hokkaido University; University of Alberta","keywords":"Task (project management); Statute; Computer science; Logical consequence; Competition (biology); Component (thermodynamics); Common law; Task group; Information retrieval; Natural language processing; Law; Political science; Artificial intelligence; Economics; Engineering","score_opus":0.04004910666469563,"score_gpt":0.3822646249559034,"score_spread":0.3422155182912078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390822940","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029389465,0.10550228,0.20526393,0.11333218,0.07437903,0.008207653,0.08633679,0.025520913,0.35206774],"genre_scores_gemma":[0.058001716,0.027985487,0.24288052,0.026069382,0.013621752,0.00513371,0.32668218,0.020121645,0.27950352],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.96818084,0.009393594,0.0021027864,0.0030575106,0.014359417,0.0029059744],"domain_scores_gemma":[0.9488535,0.011989609,0.001024044,0.0038600806,0.026789447,0.0074833543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.048638273,0.0033439256,0.0032848842,0.011844624,0.0056910235,0.013626186,0.006958644,0.0048919264,0.048961774],"category_scores_gemma":[0.046912536,0.0011897071,0.0027817225,0.014252461,0.0023886464,0.009574952,0.008823786,0.004844642,0.033306904],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020383685,0.00025737233,0.00046355044,0.00078197615,0.00005179943,0.000056445886,0.00020044332,0.0011424173,0.0011596417,0.004829148,0.8806476,0.110205814],"study_design_scores_gemma":[0.00009647537,0.00017863698,0.002042483,0.00037801385,0.000029823981,0.0001403699,0.0002420418,0.0036046742,0.0017661676,0.005096881,0.9863354,0.0000889967],"about_ca_topic_score_codex":0.04130096,"about_ca_topic_score_gemma":0.09139119,"teacher_disagreement_score":0.048961774,"about_ca_system_score_codex":0.010329834,"about_ca_system_score_gemma":0.015727002,"threshold_uncertainty_score":0.25722682},"labels":[],"label_agreement":null},{"id":"W4392926280","doi":"10.1007/s12626-024-00159-1","title":"Preface of Special Issue on 10th Competition on Legal Information of Extraction and Entailment (COLIEE 2023)","year":2024,"lang":"en","type":"article","venue":"The Review of Socionetwork Strategies","topic":"European and International Contract Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Logical consequence; Competition (biology); Extraction (chemistry); Political science; Epistemology; Philosophy; Chemistry; Chromatography; Biology","score_opus":0.018054464331107307,"score_gpt":0.33307275652991836,"score_spread":0.31501829219881106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392926280","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040654364,0.023718152,0.0016961005,0.06481507,0.8119759,0.00027432645,0.003533231,0.0002901502,0.09329048],"genre_scores_gemma":[0.0052454555,0.019544346,0.0019999784,0.03477618,0.40063813,0.0004118796,0.0063697654,0.00085255416,0.53016174],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964728,0.0004525159,0.00021784565,0.00031862254,0.0021654144,0.00037277298],"domain_scores_gemma":[0.9814555,0.004622637,0.0010578935,0.0010366689,0.009444966,0.0023823916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048944056,0.0014419251,0.00150908,0.0076828618,0.0032380924,0.008967698,0.0025177572,0.0065342174,0.20250149],"category_scores_gemma":[0.01951336,0.0005889702,0.0011996204,0.004644479,0.0012962408,0.0048498125,0.0038381587,0.007581509,0.07083056],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009909474,0.000010445899,0.00001518073,0.00006429425,0.0000015061391,0.0000073099445,0.000007929204,0.000012336962,0.00003830696,0.0006633719,0.99380904,0.0053603277],"study_design_scores_gemma":[0.00000847122,0.000016614593,0.0005062801,0.00032804743,0.000005516252,0.00002849439,0.000031674284,0.00005177008,0.00007749746,0.0014536617,0.9974826,0.000009424121],"about_ca_topic_score_codex":0.01697529,"about_ca_topic_score_gemma":0.025731862,"teacher_disagreement_score":0.20250149,"about_ca_system_score_codex":0.004519578,"about_ca_system_score_gemma":0.007536166,"threshold_uncertainty_score":0.677435},"labels":[],"label_agreement":null},{"id":"W4408404259","doi":"10.1007/s12626-025-00181-x","title":"An Advanced Deep Learning Framework for Skin Cancer Classification","year":2025,"lang":"en","type":"article","venue":"The Review of Socionetwork Strategies","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Cancer; Computer science; Skin cancer; Deep learning; Artificial intelligence; Medicine","score_opus":0.02182250615061434,"score_gpt":0.3658657292189873,"score_spread":0.344043223068373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408404259","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":[0.041874617,0.018342124,0.91983265,0.004587097,0.0007545349,0.00021913428,0.0029807307,0.0033413526,0.008067826],"genre_scores_gemma":[0.5540701,0.01207065,0.39985693,0.0025522148,0.0010010037,0.00054195937,0.008249445,0.0002679204,0.021389874],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99970514,0.00008893154,0.000020724316,0.00006282803,0.000069528636,0.00005285275],"domain_scores_gemma":[0.9996246,0.00015151798,0.000024639137,0.000027758884,0.00013962232,0.00003182171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009329635,0.000798961,0.0007878434,0.00090542366,0.0003432447,0.0009776563,0.0015512591,0.0010024494,0.0031020066],"category_scores_gemma":[0.0013191829,0.00025214898,0.00082113117,0.0008249965,0.00021372079,0.0008030625,0.0010172189,0.00158401,0.0014221321],"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":[0.00011354985,0.0002626973,0.004706654,0.00027079514,0.0001853008,0.000091921625,0.00006394628,0.11419937,0.0014676314,0.0076847435,0.028940631,0.8420127],"study_design_scores_gemma":[0.00001100234,0.00005311961,0.0008619525,0.000079065,0.000043593856,0.000057791483,0.000028592003,0.9797102,0.0008004878,0.011736083,0.0066074007,0.000010703816],"about_ca_topic_score_codex":0.016004415,"about_ca_topic_score_gemma":0.02352164,"teacher_disagreement_score":0.016004415,"about_ca_system_score_codex":0.00085204444,"about_ca_system_score_gemma":0.0013225186,"threshold_uncertainty_score":0.031822503},"labels":[],"label_agreement":null}]}