{"id":"W2998036413","doi":"10.1016/j.jelectrocard.2019.12.013","title":"Derivation and validation of the Montreal prehospital ST-elevation myocardial infarction activation rule","year":2019,"lang":"en","type":"article","venue":"Journal of Electrocardiology","topic":"Acute Myocardial Infarction Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ottawa Hospital; Université de Montréal; Centre Intégré de Santé et de Services Sociaux des Laurentides; Centre Hospitalier de l’Université de Montréal; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; McGill University; Hôpital du Sacré-Cœur de Montréal; Jewish General Hospital; Sante Montreal","funders":"","keywords":"Medicine; Myocardial infarction; Chest pain; Cohort; Emergency department; Logistic regression; Retrospective cohort study; Internal medicine; Cardiology; Electrocardiography; Emergency medicine; Derivation; Cohort study; Cardiac catheterization; Emergency medical services; Clinical prediction rule","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":[0.006305135,0.0006860714,0.0006685695,0.002100887,0.0006750913,0.002260868,0.002361691,0.0009480755,0.002980005],"category_scores_gemma":[0.06194362,0.0002947353,0.0007168364,0.0009747748,0.0004292807,0.0007147483,0.001010213,0.0009347461,0.001187625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008339413,"about_ca_system_score_gemma":0.003552239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04813252,"about_ca_topic_score_gemma":0.05975104,"domain_scores_codex":[0.99602,0.001229805,0.0004667267,0.0007511025,0.001306134,0.0002262856],"domain_scores_gemma":[0.9810951,0.009299803,0.001040402,0.002016491,0.006150885,0.0003973309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002250948,0.0004863288,0.4943901,0.0004078236,0.001058832,0.00212601,0.0005550644,0.06110311,0.0062254,0.01310995,0.02939286,0.3888936],"study_design_scores_gemma":[0.0006595476,0.0005423962,0.2059729,0.0003685074,0.0008233864,0.003162773,0.0003743399,0.7309428,0.01895644,0.01210786,0.02593243,0.0001566109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.681998,0.001966628,0.2740844,0.001507662,0.0005866574,0.001248653,0.01417687,0.002432794,0.02199825],"genre_scores_gemma":[0.9061622,0.0002515728,0.08534105,0.0001843277,0.0001182115,0.0002160608,0.005985891,0.0001686546,0.001572043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04813252,"threshold_uncertainty_score":0.09570467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009479678380588993,"score_gpt":0.2654565993285258,"score_spread":0.2559769209479368,"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."}}