{"id":"W4389940435","doi":"10.1161/circ.148.suppl_1.11451","title":"Abstract 11451: Development and Validation of the CANHEART Population-Based Laboratory Prediction Models for Atherosclerotic Cardiovascular Disease","year":2023,"lang":"en","type":"article","venue":"Circulation","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto; University of Calgary; Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Cohort; Population; Myocardial infarction; Mean corpuscular volume; Internal medicine; Framingham Risk Score; Atherosclerotic cardiovascular disease; Disease; Hematocrit","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":[0.01532501,0.001129062,0.0007048106,0.001217805,0.0004989462,0.001296455,0.001558583,0.0007787829,0.002176302],"category_scores_gemma":[0.03159806,0.0003954166,0.0009442802,0.00119167,0.000325452,0.0004959537,0.001140697,0.000944701,0.0008897137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002424561,"about_ca_system_score_gemma":0.005563352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1374408,"about_ca_topic_score_gemma":0.1200118,"domain_scores_codex":[0.9967734,0.001378675,0.0001528564,0.0005013018,0.00101528,0.0001785454],"domain_scores_gemma":[0.989283,0.003288137,0.0009706471,0.001361536,0.004731193,0.000365529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001111418,0.0005097272,0.8298258,0.0001528853,0.001118289,0.0001441078,0.0002888086,0.05337533,0.0009275583,0.001183628,0.01848963,0.09287293],"study_design_scores_gemma":[0.0005993489,0.000472912,0.6315328,0.0001337416,0.0005964293,0.0001601507,0.0001270024,0.3552818,0.001300058,0.001170604,0.008557836,0.00006725535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8893057,0.0007796501,0.07176873,0.001386971,0.0002461721,0.001716937,0.02114544,0.001258544,0.01239194],"genre_scores_gemma":[0.9354749,0.0002654603,0.03927996,0.0002201604,0.00007756268,0.0008187428,0.02097494,0.00009766745,0.00279061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1374408,"threshold_uncertainty_score":0.2732815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03643808137937738,"score_gpt":0.2565473177624288,"score_spread":0.2201092363830515,"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."}}