{"id":"W4404898302","doi":"10.1002/sim.10277","title":"Bayesian Decision Curve Analysis With Bayesdca","year":2024,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"Provincial Health Services Authority; BC Children's Hospital; Children's Hospital Foundation","keywords":"Frequentist inference; Computer science; Bayesian probability; Workflow; Machine learning; Decision analysis; False positives and false negatives; False positive paradox; Probabilistic logic; Bayes' theorem; Artificial intelligence; Data mining; Bayesian inference; Statistics; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0118945,0.0001900309,0.001100183,0.00135171,0.00007440249,0.00005846652,0.0002032951,0.00009383033,0.002705851],"category_scores_gemma":[0.003958567,0.000181611,0.00005058617,0.001341576,0.0001478976,0.0001776657,0.00002665618,0.0002668968,0.0006910398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004244133,"about_ca_system_score_gemma":0.0001188834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001490768,"about_ca_topic_score_gemma":0.002769291,"domain_scores_codex":[0.9958165,0.0001612565,0.00288179,0.0006158678,0.0001802004,0.000344416],"domain_scores_gemma":[0.9954488,0.003364559,0.0004918065,0.000462384,0.00005745364,0.0001750171],"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":[0.00003758808,0.00005796064,0.1162489,0.0005386512,0.0005605739,0.00009581945,0.003907466,0.00153538,5.727834e-7,0.7544661,0.118437,0.004114062],"study_design_scores_gemma":[0.001598898,0.0004456381,0.09471374,0.0009411497,0.0002340668,0.00001531488,0.00160185,0.4187906,8.083547e-7,0.3786723,0.1023413,0.0006443682],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003841609,0.004430865,0.9705925,0.01286457,0.0007226255,0.0003309714,0.0007376445,0.00005832763,0.006420874],"genre_scores_gemma":[0.8661509,0.0005952517,0.1255179,0.005101915,0.000651087,0.00008042403,0.0003550816,0.00006595291,0.001481506],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8623093,"threshold_uncertainty_score":0.9982058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1734663015886808,"score_gpt":0.4589526291861392,"score_spread":0.2854863275974584,"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."}}