{"meta":{"query_hash":"ea0aa16d2fbe","filters":{"venue":"Handbook of statistics"},"cohort_total":8,"direct_labels_cover":0,"predictions_cover":8,"exported":8,"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/ea0aa16d2fbe","api":"https://metacan.xera.ac/api/v1/cohort?venue=Handbook+of+statistics"},"results":[{"id":"W1498707895","doi":"10.1016/s0169-7161(07)27016-6","title":"16 Sequential and Group Sequential Designs in Clinical Trials: Guidelines for Practitioners","year":2007,"lang":"en","type":"book-chapter","venue":"Handbook of statistics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Sample size determination; Null hypothesis; Sample (material); Computer science; Set (abstract data type); Type I and type II errors; Treatment and control groups; Statistics; Mathematics","score_opus":0.9213858095193868,"score_gpt":0.6772586835422912,"score_spread":0.24412712597709552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1498707895","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00037243371,0.06254994,0.8804106,0.015852664,0.003829962,0.0025746769,0.0038321214,0.002186461,0.02839106],"genre_scores_gemma":[0.0029996973,0.041748196,0.9251535,0.0074906703,0.0017004827,0.0063277497,0.0013835358,0.0009204267,0.012275714],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9719901,0.021326408,0.0023999498,0.0007057728,0.0033525594,0.00022522974],"domain_scores_gemma":[0.9007209,0.08635011,0.002566114,0.0032647683,0.006410286,0.0006878853],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03738687,0.0028349024,0.003523114,0.0039837435,0.00058951124,0.003226021,0.0036972414,0.004590091,0.029707793],"category_scores_gemma":[0.08965458,0.002215272,0.0018528345,0.007469515,0.0026324664,0.003265085,0.0015496749,0.009384337,0.017441757],"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":[0.00018457798,0.00021900634,0.0002520722,0.0062808995,0.00019284674,0.00016413763,0.00067262194,0.0052970285,0.0004915761,0.1371841,0.50107974,0.34798145],"study_design_scores_gemma":[0.0003675196,0.00027304227,0.00059575436,0.005083816,0.00016177497,0.0008012159,0.0001854791,0.007056006,0.0006401095,0.4062656,0.578461,0.00010872114],"about_ca_topic_score_codex":0.0022473221,"about_ca_topic_score_gemma":0.005643067,"teacher_disagreement_score":0.9626131,"about_ca_system_score_codex":0.0018998429,"about_ca_system_score_gemma":0.008317332,"threshold_uncertainty_score":0.19772297},"labels":[],"label_agreement":null},{"id":"W1538865552","doi":"10.1016/s0169-7161(03)23031-5","title":"An Increasing Hazard Cure Model","year":2003,"lang":"en","type":"book-chapter","venue":"Handbook of statistics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland","keywords":"Hazard; Maximization; Nonparametric statistics; Generalization; Econometrics; Proportional hazards model; Estimation; Statistics; Hazard ratio; Expectation–maximization algorithm; Computer science; Mathematics; Maximum likelihood; Mathematical optimization; Confidence interval; Economics","score_opus":0.4943622739795478,"score_gpt":0.5149359608922042,"score_spread":0.020573686912656375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1538865552","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":[0.0031114744,0.005942183,0.92009246,0.00455593,0.0006108581,0.000058541656,0.00091461174,0.000568973,0.064144894],"genre_scores_gemma":[0.25509325,0.017631743,0.397251,0.0036713472,0.0023466882,0.00071308535,0.002367944,0.00084801315,0.320077],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99941516,0.00027997844,0.000018815917,0.00010487432,0.00013025782,0.000050997973],"domain_scores_gemma":[0.9989041,0.0007164349,0.000060942042,0.00012972397,0.00013648762,0.000052304265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020299628,0.00088573317,0.0013211261,0.0009637815,0.00047332546,0.0014745846,0.002067482,0.0016242184,0.016388314],"category_scores_gemma":[0.005006682,0.00057517336,0.0012863054,0.0012872148,0.000902862,0.0015634126,0.0010204517,0.004507447,0.0051041874],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040743787,0.000055398865,0.0005378398,0.00010638513,0.00006300322,0.00011113261,0.0001247339,0.059418842,0.00020223192,0.75092405,0.063451014,0.12496464],"study_design_scores_gemma":[0.000022498376,0.00003380706,0.00033888035,0.000059979997,0.00004786986,0.0002423798,0.000022281603,0.14967428,0.00012349915,0.7951457,0.05426137,0.000027446678],"about_ca_topic_score_codex":0.003103275,"about_ca_topic_score_gemma":0.003726958,"teacher_disagreement_score":0.016388314,"about_ca_system_score_codex":0.0010212025,"about_ca_system_score_gemma":0.0014944695,"threshold_uncertainty_score":0.054824412},"labels":[],"label_agreement":null},{"id":"W2107227780","doi":"10.1016/b978-0-444-53858-1.00023-5","title":"Time Series Analysis with R","year":2012,"lang":"en","type":"book-chapter","venue":"Handbook of statistics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Series (stratigraphy); Computer science; Time series; Autoregressive conditional heteroskedasticity; Wavelet; Code (set theory); State space; Applied mathematics; Algorithm; Mathematics; Artificial intelligence; Econometrics; Statistics; Machine learning; Programming language","score_opus":0.019284362733121948,"score_gpt":0.17953582060657106,"score_spread":0.1602514578734491,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107227780","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":[0.0005311557,0.019719597,0.9148323,0.0020445143,0.0020156272,0.0002133871,0.010256955,0.022394143,0.02799235],"genre_scores_gemma":[0.022549307,0.018443208,0.8919556,0.0011885675,0.002860038,0.0013286023,0.015752587,0.010217434,0.0357046],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957949,0.001608387,0.00059206673,0.00080357055,0.0010771797,0.00012384406],"domain_scores_gemma":[0.98797065,0.0059680743,0.0006839384,0.0036568858,0.0015644059,0.00015599892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004269738,0.0032050156,0.0044843275,0.0045523737,0.00077090156,0.0050576995,0.0027110556,0.0019109806,0.06238041],"category_scores_gemma":[0.019283723,0.0015180028,0.0021948863,0.0056656487,0.0016575317,0.0031834291,0.0018567966,0.004460695,0.092944115],"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":[0.00006886349,0.00006175086,0.0005912023,0.0018325121,0.0003266387,0.00019655869,0.00016775815,0.008101774,0.0012885011,0.2111961,0.4208659,0.35530248],"study_design_scores_gemma":[0.00009842425,0.00006554781,0.0012546699,0.00061014644,0.0001700346,0.00057956093,0.00006964896,0.030538043,0.001938643,0.3456128,0.61895585,0.00010670319],"about_ca_topic_score_codex":0.00219975,"about_ca_topic_score_gemma":0.0019849837,"teacher_disagreement_score":0.06238041,"about_ca_system_score_codex":0.0007253993,"about_ca_system_score_gemma":0.0022820255,"threshold_uncertainty_score":0.20868325},"labels":[],"label_agreement":null},{"id":"W22277511","doi":"10.1016/s0169-7161(09)00226-0","title":"Estimating Functions and Survey Sampling","year":2009,"lang":"en","type":"book-chapter","venue":"Handbook of statistics","topic":"Water Quality and Resources Studies","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Estimating equations; Statistics; Estimator; Applied mathematics; Estimation theory; Likelihood function","score_opus":0.10804258285355203,"score_gpt":0.2653341522552321,"score_spread":0.15729156940168007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W22277511","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":[0.00034718885,0.01069977,0.9649514,0.0007142761,0.0003917523,0.00007764426,0.0010937839,0.0011222056,0.020602046],"genre_scores_gemma":[0.012550352,0.02216632,0.9074101,0.0009254954,0.0009414165,0.0006172076,0.0042889854,0.0012687403,0.049831457],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973429,0.0012954462,0.00018040814,0.00038109667,0.00072344684,0.000076791635],"domain_scores_gemma":[0.9940246,0.0041945907,0.00011220179,0.0009441065,0.0006798588,0.000044724526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037372378,0.0018951325,0.002830136,0.0028123134,0.00065763394,0.0026616596,0.0029731747,0.001830534,0.021753065],"category_scores_gemma":[0.014097897,0.0020135543,0.0013566596,0.004888086,0.0017133761,0.002715259,0.0013747992,0.003477935,0.016255721],"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":[0.000014973085,0.000060872357,0.00068387616,0.0004919865,0.00008211372,0.000056538935,0.00021331233,0.015243299,0.0004805695,0.22431813,0.17673334,0.58162093],"study_design_scores_gemma":[0.000015050877,0.00003814674,0.0017154302,0.0003710267,0.000066431276,0.0005164039,0.00009752638,0.04380847,0.0009825418,0.51510173,0.43721682,0.00007050683],"about_ca_topic_score_codex":0.006168372,"about_ca_topic_score_gemma":0.009802126,"teacher_disagreement_score":0.021753065,"about_ca_system_score_codex":0.0013590882,"about_ca_system_score_gemma":0.0019011036,"threshold_uncertainty_score":0.07277125},"labels":[],"label_agreement":null},{"id":"W2770616710","doi":"10.1016/b978-0-444-53859-8.00003-5","title":"The Cross-Entropy Method for Optimization","year":2013,"lang":"en","type":"book-chapter","venue":"Handbook of statistics","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":176,"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 Montréal","funders":"","keywords":"Cross-entropy method; Heuristics; Cross entropy; Mathematical optimization; Entropy (arrow of time); Minification; Kullback–Leibler divergence; Computer science; Optimization problem; Mathematics; Algorithm; Principle of maximum entropy; Artificial intelligence; Quadratic assignment problem","score_opus":0.03155202280743595,"score_gpt":0.30178304854887317,"score_spread":0.2702310257414372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2770616710","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":[0.00040882718,0.032568686,0.94777066,0.0007657794,0.00071757426,0.00002059685,0.0003026021,0.0004156595,0.017029626],"genre_scores_gemma":[0.04251924,0.058776323,0.85271627,0.0012084426,0.0041157124,0.00040826167,0.0011352202,0.0014954897,0.037625026],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989737,0.00039923858,0.000059888902,0.00015700315,0.00037310141,0.000036997393],"domain_scores_gemma":[0.99826556,0.0012993403,0.000059443497,0.00016684066,0.0001798177,0.000029013718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017070385,0.0016669227,0.0023733196,0.0015638854,0.00043681153,0.0022684422,0.0017909638,0.002012467,0.010257003],"category_scores_gemma":[0.0043833437,0.0008531717,0.001289114,0.003363264,0.001887944,0.0027392413,0.0012224131,0.0045239716,0.005203357],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002430115,0.000054327364,0.00018746972,0.0006239903,0.00011314796,0.00006277862,0.00009792877,0.0373918,0.0011797465,0.6515506,0.06530896,0.24340506],"study_design_scores_gemma":[0.000013656949,0.000027887343,0.00039024482,0.00018537256,0.00004334755,0.00014344056,0.000021307833,0.13299467,0.0008183238,0.7646277,0.10067172,0.00006224814],"about_ca_topic_score_codex":0.0020823544,"about_ca_topic_score_gemma":0.002463948,"teacher_disagreement_score":0.010257003,"about_ca_system_score_codex":0.000977052,"about_ca_system_score_gemma":0.0012034911,"threshold_uncertainty_score":0.034313083},"labels":[],"label_agreement":null},{"id":"W4254482864","doi":"10.1016/s0169-7161(09)00230-2","title":"Empirical Likelihood Methods","year":2009,"lang":"en","type":"book-chapter","venue":"Handbook of statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.044453926400318935,"score_gpt":0.35189998708337017,"score_spread":0.30744606068305125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254482864","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":[0.0005472854,0.05632017,0.82371265,0.0018257685,0.0017328504,0.00012522191,0.0019950562,0.0030622878,0.110678755],"genre_scores_gemma":[0.023333928,0.06472132,0.7447082,0.001775101,0.0034636303,0.0007198854,0.0057982327,0.0033412555,0.15213849],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99814546,0.00056356366,0.000114414564,0.00031187088,0.0008009388,0.00006377538],"domain_scores_gemma":[0.996485,0.0022929676,0.00008928071,0.000493066,0.0005842931,0.000055341156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022157002,0.0022839077,0.0030504037,0.0030234766,0.00079504057,0.0038357542,0.0032969492,0.0025549326,0.053898633],"category_scores_gemma":[0.008895731,0.001546717,0.0013046141,0.004724769,0.0016801025,0.0037874107,0.0019024813,0.00530512,0.04406283],"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":[0.000022840766,0.000105547464,0.00030203123,0.00074665673,0.00009616834,0.00009580511,0.00017682265,0.005740079,0.0006336591,0.32604465,0.2927902,0.37324548],"study_design_scores_gemma":[0.000018524688,0.000024217288,0.0005272613,0.00040282414,0.000046194018,0.00044360466,0.00005427704,0.017944768,0.00071842404,0.44708973,0.5326685,0.00006175927],"about_ca_topic_score_codex":0.002197367,"about_ca_topic_score_gemma":0.0029480571,"teacher_disagreement_score":0.053898633,"about_ca_system_score_codex":0.0011955884,"about_ca_system_score_gemma":0.0018095882,"threshold_uncertainty_score":0.18030888},"labels":[],"label_agreement":null},{"id":"W4410737743","doi":"10.1016/bs.host.2025.04.002","title":"Combining information from multiple sources in official statistics","year":2025,"lang":"en","type":"book-chapter","venue":"Handbook of statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Statistics; Computer science; Mathematics","score_opus":0.0630197113371947,"score_gpt":0.3105441487303794,"score_spread":0.2475244373931847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410737743","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":[0.0010257952,0.041221827,0.78424305,0.0052691214,0.00217384,0.00008052208,0.0022524707,0.0023090034,0.16142437],"genre_scores_gemma":[0.04223817,0.08626521,0.6933337,0.0032936046,0.0056064767,0.00044562356,0.005892714,0.0040943096,0.15883018],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99705875,0.0011058109,0.00015719477,0.00022335895,0.0013696312,0.00008518994],"domain_scores_gemma":[0.99116725,0.0069208806,0.00019550107,0.0006458018,0.0009929264,0.00007765239],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033547957,0.000982709,0.0015048613,0.003377418,0.00070167775,0.004274095,0.001434706,0.0011193687,0.02195748],"category_scores_gemma":[0.014285425,0.0008723933,0.00053556124,0.010214245,0.0015071514,0.0051973504,0.0012037411,0.0028603314,0.013531265],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018215369,0.000038946084,0.00029762642,0.00038054658,0.000041540607,0.000053865617,0.00026025053,0.0028060752,0.00018973286,0.4424346,0.20774521,0.34573346],"study_design_scores_gemma":[0.00000585976,0.000013526708,0.00043813084,0.00032184302,0.000026784084,0.00013112855,0.00008879357,0.0069040977,0.0004013739,0.6046235,0.38701177,0.000033222255],"about_ca_topic_score_codex":0.0029524362,"about_ca_topic_score_gemma":0.007493798,"teacher_disagreement_score":0.02195748,"about_ca_system_score_codex":0.0010667956,"about_ca_system_score_gemma":0.0027466372,"threshold_uncertainty_score":0.073455095},"labels":[],"label_agreement":null},{"id":"W4412621057","doi":"10.1016/bs.host.2025.04.003","title":"Active learning of computer experiment with both quantitative and qualitative inputs","year":2025,"lang":"en","type":"book-chapter","venue":"Handbook of statistics","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","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":"Queen's University","funders":"","keywords":"Computer science; Artificial intelligence","score_opus":0.026381038918473338,"score_gpt":0.3044409708634153,"score_spread":0.278059931944942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412621057","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":[0.002645389,0.00097110105,0.9856806,0.00024045997,0.00004296356,0.000051944975,0.00006502572,0.00031563526,0.009986974],"genre_scores_gemma":[0.23223542,0.002246041,0.75007194,0.00026679024,0.00022484038,0.0007372412,0.00028176542,0.00031028033,0.013625761],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99779665,0.0012877306,0.00008472284,0.00035652643,0.0004245934,0.000049728296],"domain_scores_gemma":[0.98129004,0.016539278,0.00037165533,0.001335032,0.00033604322,0.00012787597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004281403,0.0008614689,0.0010927223,0.0010861544,0.00030676936,0.0030532978,0.0019802134,0.0011226877,0.0077004153],"category_scores_gemma":[0.018317575,0.00072056946,0.0005867279,0.0013500436,0.0031935894,0.004859806,0.0016235876,0.0017974096,0.0012650429],"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":[0.00011803304,0.0001701204,0.0016251483,0.0009242559,0.00013968624,0.000059805225,0.0006035392,0.09413449,0.003587388,0.5055508,0.0055560116,0.38753077],"study_design_scores_gemma":[0.000021524393,0.000055782657,0.0004442992,0.00011177602,0.000023199404,0.00007114911,0.00007924021,0.36186317,0.0028780745,0.6252107,0.009218692,0.000022337046],"about_ca_topic_score_codex":0.0005020002,"about_ca_topic_score_gemma":0.0008497528,"teacher_disagreement_score":0.0077004153,"about_ca_system_score_codex":0.0008619567,"about_ca_system_score_gemma":0.00084440666,"threshold_uncertainty_score":0.025760472},"labels":[],"label_agreement":null}]}