{"id":"W2749237168","doi":"10.1503/cmaj.733261","title":"Beware selection bias","year":2017,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Maternal and Perinatal Health Interventions","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"","keywords":"Selection (genetic algorithm); Population; Front line; Computer science; Selection bias; Data science; Medicine; Artificial intelligence; Political science; Pathology; Environmental health; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.14406,0.0008533612,0.002351515,0.003296008,0.002111663,0.004328757,0.002197751,0.007731857,0.02206883],"category_scores_gemma":[0.5291234,0.000575153,0.001011836,0.003373679,0.00332004,0.005601807,0.002548522,0.007074302,0.005464545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002820646,"about_ca_system_score_gemma":0.005152743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002376252,"about_ca_topic_score_gemma":0.00416295,"domain_scores_codex":[0.8034753,0.1399063,0.01845537,0.009418123,0.02571378,0.003031137],"domain_scores_gemma":[0.5153732,0.3518314,0.04921195,0.04915762,0.03000578,0.004420147],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008044938,0.0001392499,0.04520695,0.002845024,0.0007223513,0.00193178,0.005733036,0.0002684278,0.0003767253,0.05270041,0.7107365,0.1785351],"study_design_scores_gemma":[0.001077202,0.000288619,0.02418115,0.01834093,0.0007537489,0.01055463,0.00394625,0.00587948,0.001940876,0.1750281,0.7577795,0.000229625],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01634134,0.01987282,0.05831588,0.7889547,0.05882506,0.005514573,0.004002946,0.0007655051,0.04740718],"genre_scores_gemma":[0.2127836,0.00647366,0.04015462,0.6594836,0.05675822,0.008149185,0.0009562221,0.0004723728,0.01476857],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.85594,"threshold_uncertainty_score":0.7618713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03797052707158331,"score_gpt":0.3259220883532467,"score_spread":0.2879515612816634,"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."}}