{"id":"W2922770581","doi":"10.1016/j.cjca.2019.03.002","title":"Statin Use in Primary Prevention: A Simple Trial-Based Approach Compared With Guideline-Recommended Risk Algorithms for Selection of Eligible Patients","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Lipoproteins and Cardiovascular Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut universitaire de cardiologie et de pneumologie de Québec; Université Laval; Hamilton Health Sciences; McMaster University; Population Health Research Institute","funders":"Canadian Institutes of Health Research; Merck Sharp and Dohme; Novo Nordisk; National Institute for Health and Care Research; Novartis; Schering-Plough; Sanofi; Merck; GlaxoSmithKline; Bristol-Myers Squibb; Eli Lilly and Company; AstraZeneca; Bayer; Pfizer","keywords":"Medicine; Guideline; Statin; Selection (genetic algorithm); Primary prevention; Hydroxymethylglutaryl-CoA Reductase Inhibitors; Simple (philosophy); Algorithm; Secondary prevention; Intensive care medicine; Machine learning; Internal medicine; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.02186052,0.00177812,0.008391798,0.001739698,0.0008699786,0.003335149,0.001409347,0.003257827,0.005459707],"category_scores_gemma":[0.04514829,0.0008690734,0.004140791,0.001867062,0.0007697513,0.003293366,0.001875594,0.002168006,0.0007968867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008936074,"about_ca_system_score_gemma":0.001837753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009980586,"about_ca_topic_score_gemma":0.002843272,"domain_scores_codex":[0.9724572,0.01866092,0.004024793,0.002333889,0.002053278,0.0004698758],"domain_scores_gemma":[0.9702721,0.02069124,0.003818375,0.001619867,0.002002476,0.001595918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.6281232,0.006936569,0.1801808,0.003790215,0.03006899,0.0003941815,0.0004517534,0.005017572,0.002301378,0.001915057,0.006107156,0.1347131],"study_design_scores_gemma":[0.398737,0.09343957,0.339205,0.002127528,0.05146267,0.001191865,0.0007597685,0.08734138,0.002438335,0.01336278,0.009276435,0.0006577444],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9264689,0.01405705,0.02297613,0.006122889,0.002284878,0.0141165,0.00228276,0.0004481903,0.01124278],"genre_scores_gemma":[0.9666857,0.001247361,0.02371909,0.001870505,0.0006669197,0.004108656,0.0009090299,0.00005003718,0.000742851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02186052,"threshold_uncertainty_score":0.1156109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03118670769655648,"score_gpt":0.2827005051054868,"score_spread":0.2515137974089303,"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."}}