{"id":"W4220699641","doi":"10.5539/ijsp.v11n3p9","title":"Bayesian Bivariate Cure Rate Models Using Copula Functions","year":2022,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Copula (linguistics); Bivariate analysis; Weibull distribution; Statistics; Bayesian probability; Mathematics; Survival function; Joint probability distribution; Marginal distribution; Econometrics; Applied mathematics; Survival analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001431424,0.00009631018,0.0001643267,0.0001177032,0.0001911553,0.0001495997,0.0005252733,0.00002380764,0.00005496099],"category_scores_gemma":[0.00007507115,0.00008699474,0.0000559381,0.0001225753,0.00004483173,0.0003580982,0.0002902856,0.0002835442,2.459079e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001181414,"about_ca_system_score_gemma":0.0001969038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003131005,"about_ca_topic_score_gemma":0.000003948132,"domain_scores_codex":[0.9985403,0.0003076649,0.0004269107,0.0001867762,0.0004158365,0.0001224982],"domain_scores_gemma":[0.9987686,0.0001637824,0.0003302313,0.0001559412,0.000483286,0.00009820981],"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":[0.00009775515,0.0002110776,0.0005281962,0.00001784967,0.0001486125,0.0001173514,0.0006772798,0.03006293,0.0004625712,0.8553791,0.001379119,0.1109182],"study_design_scores_gemma":[0.0002312786,0.00007517431,0.000207781,0.000006587847,0.0000122908,0.0002026774,0.000008601261,0.4008662,0.00001362352,0.5971194,0.001188413,0.00006794935],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00229156,0.0001221385,0.9946582,0.001076567,0.001283973,0.00007775705,0.0002012412,0.000009128477,0.0002793997],"genre_scores_gemma":[0.2792974,0.00002337766,0.7203014,0.0002098587,0.00008799747,0.000002617452,0.000004035225,0.000005283773,0.00006797087],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3708033,"threshold_uncertainty_score":0.3547543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03592773821732773,"score_gpt":0.2992986381178914,"score_spread":0.2633708999005637,"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."}}