{"id":"W3182522530","doi":"10.1016/j.mayocp.2021.02.003","title":"Users’ Guide to Medical Decision Analysis","year":2021,"lang":"en","type":"review","venue":"Mayo Clinic Proceedings","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Impact","funders":"National Health and Medical Research Council","keywords":"Decision analysis; Medicine; Credibility; Decision tree; Process (computing); 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":["metaresearch","metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.04669988,0.0006968749,0.009331836,0.002074292,0.0002261136,0.0003423463,0.001557281,0.001300827,0.01208201],"category_scores_gemma":[0.07227428,0.0008010605,0.002149688,0.002959311,0.00007893046,0.0003587727,0.0005640291,0.0008939421,0.02142677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001262332,"about_ca_system_score_gemma":0.001347522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002062474,"about_ca_topic_score_gemma":0.0000642579,"domain_scores_codex":[0.9814862,0.0001834672,0.01481986,0.002159252,0.0005022206,0.0008490262],"domain_scores_gemma":[0.9875199,0.003932184,0.005933769,0.0009356504,0.0003088065,0.001369661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006914752,0.000233267,0.001209104,0.01056221,0.002547317,0.00001372757,0.0005799499,0.000002141799,3.779175e-9,0.01628414,0.8593122,0.109249],"study_design_scores_gemma":[0.0002725428,0.00006521187,0.00006900875,0.00664043,0.0006275941,0.00001577534,0.0002108205,0.0001358579,2.59715e-8,0.0005493867,0.9906661,0.0007472251],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005788921,0.9777355,0.002157773,0.006831166,0.001316247,0.001292398,0.0002755424,0.0001235322,0.01021002],"genre_scores_gemma":[0.000008453404,0.9673833,0.008091873,0.01513926,0.001287627,0.0004435953,0.0001589083,0.0001321468,0.007354806],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.1313539,"threshold_uncertainty_score":0.9999957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5281993240836094,"score_gpt":0.5696772818831523,"score_spread":0.04147795779954289,"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."}}