{"id":"W3108298016","doi":"10.1002/clc.23505","title":"Use of risk scores to identify lower and higher risk subsets among <scp>COMPASS‐eligible</scp> patients with chronic coronary syndromes. Insights from the <scp>CLARIFY</scp> registry","year":2020,"lang":"en","type":"article","venue":"Clinical Cardiology","topic":"Antiplatelet Therapy and Cardiovascular Diseases","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"Servier","keywords":"Medicine; Aspirin; Internal medicine; Stroke (engine); Myocardial infarction; Rivaroxaban; Population; Cardiology; Warfarin; Atrial fibrillation","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002142241,0.0006319478,0.0006969137,0.00167161,0.0003034414,0.001357992,0.0006668803,0.000506222,0.001682996],"category_scores_gemma":[0.00618688,0.000239353,0.0009367918,0.001781593,0.0002761487,0.0005706805,0.0009002798,0.0006352766,0.0004881965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003726926,"about_ca_system_score_gemma":0.0005758162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003936806,"about_ca_topic_score_gemma":0.004588431,"domain_scores_codex":[0.9984864,0.0006041049,0.000187589,0.0003355665,0.0002708985,0.0001153784],"domain_scores_gemma":[0.9951079,0.0009067902,0.002487222,0.0004209918,0.0004908473,0.0005862678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009191502,0.00006051694,0.9924169,0.00003003598,0.0002332145,0.00004309568,0.00004444351,0.0001579914,0.000159138,0.0001238163,0.001253409,0.00455816],"study_design_scores_gemma":[0.0002636533,0.0003139745,0.9950046,0.00002847589,0.0002222982,0.0002274232,0.0001221777,0.002341736,0.0001942783,0.0003128871,0.0009504359,0.00001810069],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916191,0.0008946825,0.0006167501,0.0004085489,0.00002908453,0.00007794031,0.004013943,0.00002603131,0.002314009],"genre_scores_gemma":[0.9907919,0.0003361604,0.001181375,0.0002043775,0.00008384957,0.00009782994,0.006862978,0.00001836349,0.0004232027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003936806,"threshold_uncertainty_score":0.01132935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03874280775650923,"score_gpt":0.2931678323105486,"score_spread":0.2544250245540394,"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."}}