{"id":"W4412008660","doi":"10.1161/circgen.124.004937","title":"Importance of Clinical, Laboratory, and Genetic Risk Factors for Incident CAD","year":2025,"lang":"en","type":"article","venue":"Circulation Genomic and Precision Medicine","topic":"Lipoproteins and Cardiovascular Health","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"National Center for Advancing Translational Sciences; National Human Genome Research Institute; National Heart, Lung, and Blood Institute","keywords":"Medicine; Internal medicine; CRFS; Myocardial infarction; Dyslipidemia; Coronary artery disease; Cardiology; Diabetes mellitus; Familial hypercholesterolemia; Disease; Cholesterol; Endocrinology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001338222,0.0001104085,0.0005713202,0.0001146049,0.0000880459,0.000004587593,0.00003862962,0.0001079643,0.00002539714],"category_scores_gemma":[0.001108315,0.00008013402,0.00008155542,0.0001409638,0.0001319368,0.00002568698,0.00002715923,0.0001166934,5.113604e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002795909,"about_ca_system_score_gemma":0.0001572991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001136114,"about_ca_topic_score_gemma":0.000009299934,"domain_scores_codex":[0.9985361,0.00009320873,0.0007643136,0.0003006152,0.0001959606,0.0001098458],"domain_scores_gemma":[0.9987049,0.0003598439,0.000268778,0.0003370569,0.000191768,0.0001377242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001135048,0.00001927842,0.8972444,0.0002143539,0.0001086334,0.000001396673,0.0002021606,0.00002050073,0.001213888,0.00008066433,0.0004156462,0.1003655],"study_design_scores_gemma":[0.002648853,0.0002173089,0.9886502,0.0001718655,0.0003194415,0.000004992196,0.00017881,0.000899424,0.00008771388,0.0006795799,0.0060799,0.00006191026],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746659,0.01133564,0.01237593,0.0003255355,0.0002729892,0.0008711132,0.00001949744,0.00001285373,0.0001204898],"genre_scores_gemma":[0.9936931,0.004481886,0.001185067,0.0003009668,0.0002257796,0.00001531624,0.00002203933,0.00001014803,0.00006570639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1003036,"threshold_uncertainty_score":0.326777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03290294306854185,"score_gpt":0.3488639086240414,"score_spread":0.3159609655554995,"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."}}