{"id":"W2058530447","doi":"10.1177/2150131910382251","title":"Identifying Patients With Ischemic Heart Disease in an Electronic Medical Record","year":2011,"lang":"en","type":"article","venue":"Journal of Primary Care & Community Health","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital; University Health Network; Institute for Clinical Evaluative Sciences; Women's College Hospital; University of Toronto","funders":"","keywords":"Medicine; Medical diagnosis; Medical record; Confidence interval; Chart; Terminology; Disease; Current Procedural Terminology; Electronic medical record; Diagnosis code; Medical history; Emergency medicine; Medical emergency; Internal medicine; Surgery; Population; Pathology; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003460392,0.0003074396,0.0003622464,0.002968248,0.0003883803,0.0008862764,0.0005523031,0.0003274838,0.001218366],"category_scores_gemma":[0.03027025,0.00013512,0.0002195733,0.002407038,0.0003342579,0.0006637676,0.0006526998,0.000236919,0.0004425048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006455348,"about_ca_system_score_gemma":0.001960227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01408828,"about_ca_topic_score_gemma":0.02046127,"domain_scores_codex":[0.9975808,0.0009395775,0.0005430568,0.0002519503,0.0006051166,0.00007945021],"domain_scores_gemma":[0.983225,0.009455039,0.004265246,0.0007917302,0.002022734,0.0002402843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002376269,0.0001313352,0.8582396,0.0005005873,0.00006755377,0.0003314831,0.001116825,0.0008889617,0.002478222,0.000278478,0.003431648,0.1322976],"study_design_scores_gemma":[0.0001516963,0.0004594769,0.9522718,0.0009627688,0.0002042752,0.001916604,0.001856353,0.02189632,0.005792421,0.001223525,0.01321751,0.00004727516],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9586186,0.001738856,0.02646795,0.001490221,0.00007213377,0.001608014,0.004329488,0.0004990051,0.00517574],"genre_scores_gemma":[0.917413,0.001133529,0.07479462,0.0005011469,0.00009456558,0.0003629231,0.004531062,0.00001770554,0.001151444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01408828,"threshold_uncertainty_score":0.02801251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0772375570848308,"score_gpt":0.4095656791203395,"score_spread":0.3323281220355087,"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."}}