{"id":"W2738082160","doi":"10.1016/j.cjca.2017.07.011","title":"Importance of Optimization of Cardiovascular Risk Factors and Lifestyle Behaviours","year":2017,"lang":"en","type":"letter","venue":"Canadian Journal of Cardiology","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Libin Cardiovascular Institute of Alberta; University of Calgary","funders":"","keywords":"Medicine; Myocardial infarction; Framingham Heart Study; Framingham Risk Score; Stroke (engine); Disease; Population; Risk factor; Internal medicine; Gerontology; Demography; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001013594,0.0003234981,0.002865196,0.000701542,0.0001190485,0.00001160092,0.0002647102,0.001014993,0.00001272659],"category_scores_gemma":[0.0008285005,0.0002596331,0.002170229,0.0000914464,0.0005744261,0.00007139714,0.0000190055,0.001686667,3.618275e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001780075,"about_ca_system_score_gemma":0.003089095,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01388542,"about_ca_topic_score_gemma":0.0004882242,"domain_scores_codex":[0.9975321,0.0003577722,0.0009243886,0.0002805469,0.0004361827,0.0004689898],"domain_scores_gemma":[0.9960889,0.0001168452,0.00144367,0.0009399335,0.0007458447,0.0006648187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003673581,0.000001868056,0.8452196,0.0003953009,0.006194687,0.002241106,0.0001307453,0.01230511,0.000001285734,0.000001058975,0.1321756,0.001296964],"study_design_scores_gemma":[0.001688212,0.0005784716,0.3283494,0.0004169514,0.00913387,0.003262023,0.0000724144,0.00001309623,0.00004861039,0.00001334079,0.6560847,0.0003389247],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.88754,0.0797823,0.004016524,0.01974193,0.004780444,0.001136792,0.001364421,0.00001291348,0.001624681],"genre_scores_gemma":[0.9755079,0.01218146,0.0006784045,0.003702564,0.007376518,0.000004354798,0.0003270518,0.0001337246,0.00008798376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5239091,"threshold_uncertainty_score":0.9999856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01687359396816207,"score_gpt":0.2471446434074318,"score_spread":0.2302710494392698,"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."}}