{"id":"W1993169406","doi":"10.2478/demo-2014-0006","title":"Some New Random Effect Models for Correlated Binary Responses","year":2014,"lang":"en","type":"article","venue":"Dependence Modeling","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Akaike information criterion; Copula (linguistics); Mathematics; Inference; Statistics; Bernoulli's principle; Binary data; Correlation; Model selection; Bernoulli trial; Confidence interval; Bayesian information criterion; Binary number; Econometrics; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.000650824,0.0001460825,0.0002393626,0.00006058513,0.0002096047,0.00004735315,0.0001652776,0.00009791649,0.00003397489],"category_scores_gemma":[0.00252285,0.0001314276,0.00009156398,0.0001087401,0.00002473851,0.000196567,0.00002911743,0.0001212818,0.00005878316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003732148,"about_ca_system_score_gemma":0.00006130023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001878301,"about_ca_topic_score_gemma":0.000001772572,"domain_scores_codex":[0.9988481,0.00009712736,0.0003389483,0.0002683018,0.0002167208,0.0002308359],"domain_scores_gemma":[0.9969461,0.002444834,0.00008067636,0.0002732206,0.0001145559,0.0001405912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002788936,0.00003356437,0.000002954467,0.00004125364,0.00001245573,5.082879e-7,0.00005855343,0.1298632,0.0005278034,0.8652627,0.001464827,0.002453343],"study_design_scores_gemma":[0.0009650493,0.00003618584,0.00000218911,0.00002861862,0.00003284438,0.000002225283,0.000006630562,0.5684459,0.0001828997,0.430177,0.00003122627,0.00008931763],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0272324,0.00005350959,0.9711889,0.0003765667,0.00008709933,0.0005725938,0.00006192022,0.0002127909,0.0002141932],"genre_scores_gemma":[0.9507573,0.000007581831,0.0483053,0.0001241081,0.0001128411,0.0001555314,0.00006702262,0.00002336389,0.0004469085],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9235249,"threshold_uncertainty_score":0.5359462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09803342134527707,"score_gpt":0.3694102201476667,"score_spread":0.2713767988023896,"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."}}