{"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":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000027912802,0.00075626123,0.97577727,0.00009849404,0.0018831525,0.0025206034,0.007795457,0.00005273671,0.011113219],"genre_scores_gemma":[0.000007707105,0.003649296,0.9795381,0.00032104237,0.0019281801,0.000067692876,0.00019718574,0.00018494962,0.014105867],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.986918,0.0015293114,0.0091912905,0.0009566198,0.00087118935,0.00053362537],"domain_scores_gemma":[0.8231528,0.17141412,0.0035107564,0.00051235734,0.0011322588,0.00027769167],"candidate_categories":["metaresearch","metaepi_narrow","research_integrity"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.038431365,0.0006645344,0.0037394962,0.00035550157,0.00008586388,0.000063572224,0.00031090318,0.0013965999,0.00087020936],"category_scores_gemma":[0.32971692,0.00061470724,0.00057133246,0.000051485873,0.001004507,0.00007688015,0.00017028286,0.00094047165,0.000013471764],"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":[0.0014232028,0.00014416053,0.000008002683,0.00095175847,0.00045823946,0.00006401685,0.00003093167,9.890731e-7,0.00006025395,0.8433909,0.0572825,0.096185036],"study_design_scores_gemma":[0.004322943,0.0007650203,0.0000038895696,0.0020220438,0.001463,0.0000141888995,0.00002046797,0.0002931591,0.0001461462,0.9636676,0.0266995,0.0005820688],"about_ca_topic_score_codex":0.000027358547,"about_ca_topic_score_gemma":0.00017520261,"teacher_disagreement_score":0.29128557,"about_ca_system_score_codex":0.00017226108,"about_ca_system_score_gemma":0.00039029043,"threshold_uncertainty_score":0.9998998},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000042893294,0.00031325562,0.8568103,0.000018969096,0.00037737592,0.0005540132,0.0064394213,0.00008285194,0.13539954],"genre_scores_gemma":[0.000018492308,0.00090332737,0.94488704,0.0002178921,0.00024235425,0.00001239931,0.000057886056,0.00025646397,0.053404126],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99546176,0.00040055838,0.002059271,0.00070169766,0.0009395959,0.00043711546],"domain_scores_gemma":[0.97202975,0.024524286,0.001315077,0.001179328,0.00059287995,0.00035869025],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0024181472,0.0006739563,0.0019706676,0.0001668718,0.00010421876,0.00005168082,0.00048903486,0.0008954512,0.0013305739],"category_scores_gemma":[0.021998009,0.0006593751,0.0002315863,0.000033078726,0.0006052571,0.00006328459,0.00010147563,0.0008658994,0.000056675213],"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":[0.0001416386,0.000104075996,0.0000052051723,0.00061641954,0.00017234961,0.0000471264,0.000070270726,0.000027399179,0.00010171741,0.9611623,0.02964905,0.007902398],"study_design_scores_gemma":[0.0007135637,0.00028958666,0.0000010801303,0.0015086043,0.0007697997,0.000014900759,0.00000553668,0.004759377,0.0002887287,0.9868835,0.004122085,0.0006432213],"about_ca_topic_score_codex":0.0000038955905,"about_ca_topic_score_gemma":0.0000082202405,"teacher_disagreement_score":0.08807678,"about_ca_system_score_codex":0.000102483165,"about_ca_system_score_gemma":0.0002840619,"threshold_uncertainty_score":0.99958575},"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":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000016677626,0.025901133,0.14300714,0.000033921922,0.0001169926,0.00028372876,0.016033884,0.000043574844,0.8145629],"genre_scores_gemma":[0.0014401452,0.0019811809,0.025231909,0.000022691524,0.00016770637,0.000008198917,0.0008227108,0.00009451683,0.97023094],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983688,0.0000047420854,0.000917305,0.0003653685,0.00009375846,0.00025001224],"domain_scores_gemma":[0.9979219,0.000059488942,0.0012040568,0.0005711925,0.00013235233,0.00011100521],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000176072,0.00032968362,0.0015210207,0.0005540147,0.00007512105,0.000039721006,0.00018693336,0.00017119125,0.021873044],"category_scores_gemma":[0.000012195424,0.00033414003,0.00028736444,0.00012936677,0.00023387937,0.000100669124,0.0000648137,0.00014380658,0.0013950255],"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":[0.00003777894,0.000021387255,0.00085206813,0.00014049228,0.005013071,0.000010812656,0.00016933866,0.000076462624,0.0000015915297,0.98805964,0.00471264,0.0009046947],"study_design_scores_gemma":[0.00039766982,0.0003010932,0.0005916719,0.00022526499,0.0030281816,0.000010384016,0.000021104695,0.0009221728,0.000015514112,0.07715738,0.91629165,0.0010379015],"about_ca_topic_score_codex":0.00016840895,"about_ca_topic_score_gemma":0.000194031,"teacher_disagreement_score":0.911579,"about_ca_system_score_codex":0.000060065708,"about_ca_system_score_gemma":0.000026714846,"threshold_uncertainty_score":0.99991107},"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":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005551821,0.0025771938,0.44007647,0.000052096915,0.00037519686,0.00044506587,0.003869714,0.00006914695,0.55197996],"genre_scores_gemma":[0.0012742131,0.00098252,0.28306165,0.000113428134,0.00014652009,0.0000037426487,0.00039193506,0.00005756006,0.7139684],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991037,0.000019293051,0.00029454194,0.00022245878,0.00022154424,0.00013840914],"domain_scores_gemma":[0.9993326,0.00026596145,0.00018838196,0.00013915467,0.0000177048,0.000056163186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021941322,0.00017679903,0.00028396296,0.000027064083,0.00017630929,0.000017874645,0.000075067204,0.00010009822,0.0005243083],"category_scores_gemma":[0.00006463093,0.00015918682,0.000026332546,0.000012157346,0.00040455372,0.000024888019,0.00013760192,0.0001527494,0.00009035941],"study_design_candidate":"design_other","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":[0.0001857716,0.00017644238,0.01657177,0.0010617727,0.0006404607,0.00006594646,0.006444607,0.00848198,0.0005678236,0.02369873,0.10600798,0.8360967],"study_design_scores_gemma":[0.0021958144,0.0016830694,0.11458655,0.0052732145,0.0012165027,0.00008399696,0.00021976572,0.008179845,0.0002715056,0.39608413,0.4661363,0.0040693036],"about_ca_topic_score_codex":0.00023892528,"about_ca_topic_score_gemma":0.00037735858,"teacher_disagreement_score":0.83202744,"about_ca_system_score_codex":0.000034835124,"about_ca_system_score_gemma":0.0000064606884,"threshold_uncertainty_score":0.649145},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.7295902e-8,0.00093394885,0.9815952,0.00006277301,0.00036316953,0.0003246186,0.0002548731,0.000041760115,0.01642363],"genre_scores_gemma":[0.0000049124455,0.0010055299,0.860179,0.00006881493,0.00007625732,0.00002462982,0.00004097742,0.000025107687,0.13857476],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987559,0.000019570658,0.00044023813,0.00030397487,0.00026932056,0.00021104135],"domain_scores_gemma":[0.9976033,0.000737329,0.0003966464,0.0005169276,0.0006765254,0.00006927328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028254776,0.00021247043,0.00026950648,0.00004479017,0.00021508607,0.00028414984,0.000698448,0.00016961903,0.000068243644],"category_scores_gemma":[0.00008721028,0.00016023459,0.00007702554,0.000016788432,0.00013348914,0.00009621747,0.00012028839,0.00016147715,0.000035381017],"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":[0.000006324293,0.0000041086423,2.7705548e-7,0.00004144074,0.00003123151,8.0401077e-7,0.000040554114,0.0054753544,0.000011014334,0.91211396,0.010011188,0.072263755],"study_design_scores_gemma":[0.00014281285,0.0000850216,5.6361347e-7,0.0001245263,0.00002417822,0.0000023249497,5.773033e-7,0.6032497,0.0001807035,0.3780501,0.017986258,0.00015319526],"about_ca_topic_score_codex":0.000007848727,"about_ca_topic_score_gemma":0.0000021900241,"teacher_disagreement_score":0.5977744,"about_ca_system_score_codex":0.00002936595,"about_ca_system_score_gemma":0.00015342208,"threshold_uncertainty_score":0.6534177},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.0613622e-8,0.002785161,0.74082476,0.0000870364,0.00026417625,0.00014668675,0.000119419936,0.000061389466,0.25571138],"genre_scores_gemma":[6.58237e-7,0.0010547788,0.872342,0.00053061405,0.00012840045,0.000002679132,0.000019313959,0.00003571633,0.12588584],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978804,0.00011846028,0.0006472164,0.00057775836,0.00043478847,0.00034139515],"domain_scores_gemma":[0.99762607,0.00052794255,0.0004267784,0.0009401187,0.00026570685,0.00021337967],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000654455,0.00041402003,0.00079513836,0.00018755869,0.00006550954,0.00006429044,0.00088702753,0.00041351037,0.00012473887],"category_scores_gemma":[0.00007602485,0.00038323452,0.00017184833,0.000045406137,0.00013146426,0.00008639355,0.00022912784,0.0004783026,0.000047034628],"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":[0.0000031512584,0.000012133575,2.5209647e-7,0.000031736326,0.000027458596,0.000029069764,0.00009899926,2.5335464e-7,0.000041020572,0.46280375,0.014262162,0.52269],"study_design_scores_gemma":[0.00018395012,0.00021117849,0.0000059328895,0.00029956087,0.000070342925,0.000022420354,3.278492e-7,0.0016582285,0.00072663475,0.8285706,0.16789193,0.00035886932],"about_ca_topic_score_codex":0.0000024034075,"about_ca_topic_score_gemma":0.000002239581,"teacher_disagreement_score":0.5223311,"about_ca_system_score_codex":0.000047156747,"about_ca_system_score_gemma":0.00028070924,"threshold_uncertainty_score":0.99986196},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000151665345,0.00022063084,0.90751016,0.000007359005,0.00035333863,0.00041335193,0.031495765,0.000040796476,0.059943452],"genre_scores_gemma":[0.0002532602,0.00039430463,0.98525184,0.00009016599,0.000082039514,0.000015481892,0.0012733788,0.000050418006,0.012589137],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99717796,0.00007172157,0.0015796989,0.00029017733,0.0005706308,0.00030982884],"domain_scores_gemma":[0.98889756,0.0092487745,0.0009133076,0.0004042529,0.00043447837,0.00010161028],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032307935,0.00045604177,0.0010809822,0.0003282523,0.000075152566,0.00006084861,0.00029860955,0.00041344063,0.0008637301],"category_scores_gemma":[0.004572778,0.00047424124,0.00007027901,0.00005253865,0.00026974228,0.000084210384,0.00016466188,0.00059540634,0.00005044182],"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":[0.00009314231,0.000044366378,0.00009778724,0.0005691231,0.0000837639,0.000017584163,0.0006145993,0.000008940013,0.000010291393,0.90115005,0.01627985,0.081030525],"study_design_scores_gemma":[0.0009963941,0.00014592116,0.00011959021,0.0026090194,0.00021156773,8.202449e-7,0.000062600004,0.0077263275,0.00018770882,0.97524387,0.012233444,0.00046271802],"about_ca_topic_score_codex":0.00028630375,"about_ca_topic_score_gemma":0.00035723535,"teacher_disagreement_score":0.08056781,"about_ca_system_score_codex":0.000104906714,"about_ca_system_score_gemma":0.00034041982,"threshold_uncertainty_score":0.99977094},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010990976,0.0008944685,0.9849703,0.00005410875,0.000039458424,0.00027025703,0.0005168663,0.000021200432,0.013222366],"genre_scores_gemma":[0.0006134444,0.0005409182,0.97293484,0.000032734366,0.000019231133,0.000021385245,0.00007155898,0.000016152386,0.025749743],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988028,0.000048921476,0.00036905173,0.00036089763,0.00029384374,0.00012448503],"domain_scores_gemma":[0.99805635,0.00075299846,0.00051033386,0.00024169675,0.00038341715,0.000055182423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009399287,0.00022940572,0.0004406043,0.00014632527,0.000098050135,0.000019770925,0.00023101119,0.00008794942,0.000015743128],"category_scores_gemma":[0.000013830705,0.00020880823,0.00003599082,0.000053318807,0.00038094673,0.00009994468,0.00020055534,0.00021890571,0.0000026731889],"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":[0.00002742078,0.00003799249,0.0000017508783,0.00011383204,0.00016052653,0.000006124655,0.008987526,0.00008377732,0.000092004135,0.97847736,0.001219569,0.010792131],"study_design_scores_gemma":[0.006195832,0.012404224,0.0005668284,0.015384179,0.00072506693,0.00006762644,0.003912903,0.25121516,0.015884593,0.6264266,0.06354628,0.0036707267],"about_ca_topic_score_codex":0.000022654714,"about_ca_topic_score_gemma":0.000006020617,"teacher_disagreement_score":0.35205078,"about_ca_system_score_codex":0.00004190432,"about_ca_system_score_gemma":0.00020545533,"threshold_uncertainty_score":0.85149527},"labels":[],"label_agreement":null}]}