{"id":"W4361289113","doi":"10.1002/sta4.568","title":"Bayesian outcome selection modeling","year":2023,"lang":"en","type":"article","venue":"Stat","topic":"Fatty Acid Research and Health","field":"Nursing","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers; National Institute on Alcohol Abuse and Alcoholism; Australian Research Council; Canadian Institutes of Health Research; National Institutes of Health; University of Melbourne","keywords":"Outcome (game theory); Bayesian probability; Selection (genetic algorithm); Computer science; Psychology; Econometrics; Machine learning; Artificial intelligence; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002738991,0.00005435742,0.00007804034,0.0001362312,0.0002016276,0.00003030146,0.00005919766,0.00003679325,0.00008598088],"category_scores_gemma":[0.0000755588,0.00005046359,0.00003060799,0.0003768483,0.00001178185,0.00008472023,0.00001813034,0.0001790446,0.0006697548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008473323,"about_ca_system_score_gemma":0.00002346656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002955807,"about_ca_topic_score_gemma":0.0002746567,"domain_scores_codex":[0.9990984,0.00004343986,0.0001262509,0.0001372466,0.0001981464,0.0003965012],"domain_scores_gemma":[0.9997224,0.00003147685,0.00001330426,0.00008866095,0.00003400973,0.0001101143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001866445,0.0002704976,0.2486864,0.001669156,0.00009412545,0.0001212141,0.00928545,0.1219717,0.08111227,0.003009633,0.2243182,0.307595],"study_design_scores_gemma":[0.000322289,0.0001329549,0.002205067,0.00001569334,0.000003185039,0.000002849348,0.0002964432,0.9887663,0.002312289,0.00335928,0.002487475,0.00009618684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8552144,0.0001040011,0.1084719,0.02538028,0.001993835,0.0005890446,0.00002805072,0.001522728,0.006695764],"genre_scores_gemma":[0.9976357,0.00001494136,0.001362897,0.0003074872,0.0001426298,0.000007684613,0.00001851227,0.00001779663,0.0004923315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8667946,"threshold_uncertainty_score":0.8608565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07869389687444273,"score_gpt":0.3922452916117336,"score_spread":0.3135513947372909,"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."}}