{"id":"W3197078525","doi":"10.1503/cmaj.202434","title":"Implementing machine learning in medicine","year":2021,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":136,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Alberta; University of Toronto; Alberta Machine Intelligence Institute","keywords":"Computer science; Key (lock); Process (computing); Artificial intelligence; Machine learning; Computer security; Programming language","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"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":[0.01360726,0.0005958524,0.0005393432,0.0006662533,0.001827324,0.00470932,0.001800995,0.01358859,0.02479693],"category_scores_gemma":[0.07384582,0.0004207388,0.0006973682,0.0004167483,0.007247162,0.006275362,0.004335363,0.01977273,0.01405585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00431273,"about_ca_system_score_gemma":0.004928285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002862511,"about_ca_topic_score_gemma":0.004200708,"domain_scores_codex":[0.9892811,0.006541161,0.0003738799,0.0006290228,0.002574783,0.0006001234],"domain_scores_gemma":[0.9721377,0.02038563,0.0006896459,0.002023698,0.00288127,0.001882058],"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":[0.0000938119,0.0001044522,0.001035721,0.0001317832,0.00003355024,0.0003560004,0.0001361424,0.001161759,0.0001868226,0.1148811,0.6506943,0.2311846],"study_design_scores_gemma":[0.0001710881,0.0002112312,0.0007139212,0.0007259471,0.0000222655,0.0008097073,0.0001528431,0.005145152,0.000430244,0.3016639,0.6899021,0.00005171199],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0004204407,0.002957091,0.01099727,0.9529426,0.01032632,0.00003904145,0.0000307334,0.0002057643,0.02208088],"genre_scores_gemma":[0.05834719,0.009600186,0.02759562,0.8332518,0.04080483,0.0003666337,0.0001191076,0.0002013926,0.02971325],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02479693,"threshold_uncertainty_score":0.08295399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01697632968548088,"score_gpt":0.288769190964128,"score_spread":0.2717928612786471,"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."}}