{"id":"W1989052833","doi":"10.1097/01.ede.0000059227.04349.0d","title":"Improving the Prediction of Cardiovascular Risk: Interaction Between LDL and HDL Cholesterol","year":2003,"lang":"en","type":"article","venue":"Epidemiology","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal General Hospital","funders":"","keywords":"Cholesterol; Medicine; Internal medicine; Hyperlipidemia; High-density lipoprotein; Lipoprotein; Ldl cholesterol; Risk factor; Cardiology; Endocrinology; Diabetes mellitus","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":[0.007500859,0.0009953442,0.001003023,0.001336414,0.0002760823,0.001277734,0.0005366284,0.0007905595,0.0009746612],"category_scores_gemma":[0.0224328,0.0003916117,0.0008868813,0.001017314,0.000323369,0.0007768814,0.0007327945,0.00133321,0.0003890256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004319403,"about_ca_system_score_gemma":0.0009365776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005493267,"about_ca_topic_score_gemma":0.007686425,"domain_scores_codex":[0.9953739,0.003459033,0.0001759089,0.0003630487,0.0005125551,0.0001156119],"domain_scores_gemma":[0.980157,0.0164845,0.00149613,0.0007220772,0.0008153533,0.0003248718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004103539,0.0002498147,0.8674019,0.0001555834,0.001139418,0.00007112673,0.00006364204,0.02729975,0.0006314904,0.0004824642,0.001671865,0.1004226],"study_design_scores_gemma":[0.0002151886,0.001066967,0.5867123,0.0001917279,0.001987077,0.0006387152,0.00008404633,0.3937162,0.002773514,0.008444943,0.004049785,0.0001195719],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8644612,0.01387764,0.1083841,0.006293366,0.0001932583,0.0001335407,0.001537935,0.0006249881,0.004494],"genre_scores_gemma":[0.9590091,0.001891579,0.03706308,0.0004182364,0.0002490259,0.00004295724,0.0006810474,0.00002978349,0.0006151377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007500859,"threshold_uncertainty_score":0.0396688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04187423530457976,"score_gpt":0.2766492918741456,"score_spread":0.2347750565695658,"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."}}