{"id":"W2928048052","doi":"10.1016/j.cjco.2019.01.003","title":"Clinical Utility and Practical Considerations of a Coronary Artery Disease Genetic Risk Score","year":2019,"lang":"en","type":"article","venue":"CJC Open","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Western University","funders":"Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada","keywords":"Medicine; Framingham Risk Score; Confidence interval; Internal medicine; Hazard ratio; Odds ratio; Cohort; Coronary artery disease; Logistic regression; Proportional hazards model; Risk assessment; Family history; Disease","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":[],"consensus_categories":[],"category_scores_codex":[0.0988095,0.001658354,0.001975811,0.00401974,0.0004973768,0.004647695,0.002676285,0.002462005,0.002761604],"category_scores_gemma":[0.2949221,0.000679553,0.001412815,0.003024919,0.00375206,0.002225865,0.002395903,0.004347694,0.0006897847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001125845,"about_ca_system_score_gemma":0.002272676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001633661,"about_ca_topic_score_gemma":0.002031093,"domain_scores_codex":[0.8987901,0.08791137,0.003449026,0.002100189,0.007450371,0.0002988533],"domain_scores_gemma":[0.6646922,0.2998925,0.009608496,0.009472223,0.01466562,0.001669065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0045105,0.0005175194,0.4674795,0.00213187,0.004125432,0.001257133,0.001336249,0.02610579,0.002058272,0.05457924,0.02173167,0.4141669],"study_design_scores_gemma":[0.003545214,0.007051692,0.2882516,0.004972193,0.005102058,0.01118535,0.001892126,0.3223614,0.003817153,0.3061452,0.04476699,0.0009090763],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2759516,0.05117096,0.4456921,0.1899474,0.002694869,0.001178817,0.002535757,0.000895116,0.02993342],"genre_scores_gemma":[0.7746821,0.004654067,0.2098082,0.006013738,0.002748172,0.0004830422,0.0003796094,0.0001758926,0.001055142],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0988095,"threshold_uncertainty_score":0.5225608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05502119633956343,"score_gpt":0.376289185283889,"score_spread":0.3212679889443256,"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."}}