{"id":"W4417222887","doi":"10.1007/s42081-025-00322-0","title":"On multivariate binary outcomes copulas-regression problem","year":2025,"lang":"en","type":"article","venue":"Japanese Journal of Statistics and Data Science","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières; Université du Québec à Montréal","funders":"Fonds de Recherche du Québec - Santé","keywords":"Multivariate statistics; Copula (linguistics); Covariate; Binary number; Binary data; Estimator; Marginal distribution; Logistic regression; Multivariate normal distribution","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002190698,0.000120471,0.0002904871,0.000189881,0.0002515985,0.0001165404,0.000682775,0.00002592972,0.00003565522],"category_scores_gemma":[0.01118186,0.0000697431,0.00001501483,0.0003556473,0.0003978584,0.0003532008,0.0003490097,0.0001755302,0.000002501308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002623845,"about_ca_system_score_gemma":0.0001524762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002755852,"about_ca_topic_score_gemma":0.000002867822,"domain_scores_codex":[0.998486,0.00007719095,0.0004937885,0.0002475519,0.0004879176,0.0002075224],"domain_scores_gemma":[0.995746,0.003077829,0.0002864347,0.000417059,0.0003225041,0.0001501889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007710358,0.0001816233,0.002634688,0.0000670418,0.00001483134,0.00003811201,0.0003210646,0.000004385559,0.005011567,0.9584431,0.001968979,0.03123752],"study_design_scores_gemma":[0.0008388466,0.0003758938,0.08469348,0.000346164,0.0000481477,0.00003072477,0.0003936515,0.02050401,0.0002231657,0.8922471,0.0001432751,0.0001555663],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4159306,0.0000285931,0.581125,0.0006353071,0.0003900999,0.0001796472,0.0004038291,0.00001410126,0.001292752],"genre_scores_gemma":[0.4192821,0.00001794994,0.5805138,0.0001131446,0.000008231889,7.613493e-7,0.000001908147,0.000003071558,0.00005896075],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08205879,"threshold_uncertainty_score":0.9971474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1058971062364061,"score_gpt":0.4482954307905468,"score_spread":0.3423983245541407,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}