{"id":"W4392957163","doi":"10.1177/1536867x241233671","title":"A Bayesian method for addressing multinomial misclassification with applications for alcohol epidemiological modeling","year":2024,"lang":"en","type":"article","venue":"The Stata Journal Promoting communications on statistics and Stata","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multinomial distribution; Computer science; Bayesian probability; Estimation; Statistics; Data mining; Econometrics; Data science; Machine learning; Artificial intelligence; Mathematics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01682185,0.001407592,0.001351355,0.00309306,0.001350545,0.001688975,0.002940989,0.001957875,0.013925],"category_scores_gemma":[0.08519187,0.001105616,0.001487022,0.002749358,0.001169348,0.003161188,0.003670498,0.003833245,0.004826535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009569876,"about_ca_system_score_gemma":0.002950417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00592879,"about_ca_topic_score_gemma":0.006404494,"domain_scores_codex":[0.9899209,0.006673985,0.0005486863,0.0008149236,0.001868743,0.0001727388],"domain_scores_gemma":[0.9714563,0.02283477,0.001184826,0.001846044,0.002278507,0.0003994964],"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":[0.0002721402,0.0002099078,0.007996083,0.0003843902,0.0003229651,0.0003121307,0.001000611,0.05753862,0.002297518,0.2661633,0.03928047,0.6242219],"study_design_scores_gemma":[0.0001398524,0.00008637257,0.002018684,0.00022441,0.00008678327,0.000633562,0.00011606,0.6008941,0.002817431,0.3427837,0.05005768,0.0001413869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003819991,0.00006258026,0.9983584,0.0001478346,0.00002648173,0.00003267581,0.00009355267,0.000631999,0.0002644119],"genre_scores_gemma":[0.01081332,0.0001457469,0.9864818,0.0002229831,0.00007715025,0.000442309,0.0002955534,0.0004066573,0.001114497],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01682185,"threshold_uncertainty_score":0.08896351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3286245790278658,"score_gpt":0.4984497198034591,"score_spread":0.1698251407755933,"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."}}