{"id":"W4400863368","doi":"10.2196/57035","title":"Targeted Development and Validation of Clinical Prediction Models in Secondary Care Settings: Opportunities and Challenges for Electronic Health Record Data","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health records; Computer science; Quality (philosophy); Data science; Triage; Health care; Data quality; Data extraction; Process (computing); Data mining; Medicine; MEDLINE; Metric (unit); Engineering; Medical emergency","routes":{"ca_aff":false,"ca_fund":false,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3042704,0.001189856,0.001928334,0.00375373,0.001636965,0.008571584,0.006633862,0.002612754,0.002737304],"category_scores_gemma":[0.5585023,0.0008259754,0.002727899,0.004932632,0.003591501,0.007244133,0.008639488,0.005523654,0.001271347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002763264,"about_ca_system_score_gemma":0.01125741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00545434,"about_ca_topic_score_gemma":0.005107469,"domain_scores_codex":[0.703221,0.2414126,0.02131747,0.01056387,0.02185616,0.001628878],"domain_scores_gemma":[0.1809635,0.6553102,0.02863724,0.07156494,0.06046737,0.003056721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001263187,0.001925011,0.3254001,0.007237982,0.002149543,0.0008154184,0.007217266,0.03575649,0.00525068,0.02374065,0.03136438,0.5578792],"study_design_scores_gemma":[0.001274209,0.004208269,0.2191588,0.02681499,0.001643063,0.001743198,0.009767385,0.4293505,0.02424446,0.1448727,0.1362944,0.0006281023],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1724307,0.006439709,0.7484741,0.04692176,0.001313895,0.005463509,0.008980792,0.002856409,0.007119167],"genre_scores_gemma":[0.3771308,0.001724892,0.5971012,0.006644148,0.000703104,0.00548795,0.01018152,0.0004398559,0.0005864885],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3042704,"threshold_uncertainty_score":0.8579584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1490105410860406,"score_gpt":0.3951361375382488,"score_spread":0.2461255964522083,"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."}}