{"id":"W4388938597","doi":"10.1136/bmjqs-2022-015713","title":"Grand rounds in methodology: key considerations for implementing machine learning solutions in quality improvement initiatives","year":2023,"lang":"en","type":"article","venue":"BMJ Quality & Safety","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; North York General Hospital; University of Toronto","funders":"University of Toronto","keywords":"Sociotechnical system; Workflow; Computer science; Software deployment; Health care; Harm; Quality (philosophy); Key (lock); Process management; Risk analysis (engineering); Management science; Data science; Medicine; Knowledge management; Computer security; Software engineering; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.6167952,0.002017354,0.002462053,0.003251634,0.009914367,0.02352684,0.008599442,0.01521284,0.03308791],"category_scores_gemma":[0.6729239,0.00277641,0.003321842,0.003349656,0.01891618,0.01986595,0.02518929,0.01912079,0.01197362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0177441,"about_ca_system_score_gemma":0.09827098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005966689,"about_ca_topic_score_gemma":0.01305421,"domain_scores_codex":[0.2848474,0.6529527,0.01888247,0.006030289,0.03199694,0.005290288],"domain_scores_gemma":[0.264312,0.5701247,0.02204836,0.06039087,0.06744312,0.01568104],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006514162,0.0004243643,0.003895627,0.005029599,0.0003995032,0.0009619186,0.04349134,0.002369624,0.00128653,0.4485373,0.1310647,0.361888],"study_design_scores_gemma":[0.0007184729,0.001139471,0.003343326,0.01039642,0.0002134307,0.0008846905,0.02214963,0.006299424,0.002275553,0.4414815,0.5106599,0.0004381946],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.005823022,0.004211645,0.3683522,0.5405529,0.01525083,0.01125879,0.0002766771,0.0009765271,0.05329737],"genre_scores_gemma":[0.07958189,0.002710816,0.7542372,0.103549,0.004496159,0.03267586,0.000194739,0.001014188,0.02154013],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3832048,"threshold_uncertainty_score":0.4725598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6977982343209539,"score_gpt":0.59802145663961,"score_spread":0.09977677768134385,"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."}}