{"id":"W2123993085","doi":"","title":"Approach to identifying and managing atherogenic dyslipidemia: a metabolic consequence of obesity and diabetes.","year":2013,"lang":"en","type":"article","venue":"PubMed","topic":"Lipoproteins and Cardiovascular Health","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Interior Health","funders":"","keywords":"Dyslipidemia; Medicine; Fenofibrate; Internal medicine; Metabolic syndrome; Diabetes mellitus; Obesity; Endocrinology; Cholesterol; Framingham Risk Score; National Cholesterol Education Program; Triglyceride; Niacin; Disease","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":[0.004419283,0.001755594,0.00279591,0.003290808,0.0004390527,0.002048502,0.001439664,0.002462564,0.004418517],"category_scores_gemma":[0.01051813,0.0004843843,0.001893239,0.001861695,0.000617145,0.002392741,0.001002597,0.003132457,0.001669354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001978174,"about_ca_system_score_gemma":0.005597559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00395546,"about_ca_topic_score_gemma":0.008524604,"domain_scores_codex":[0.9973508,0.0008413153,0.0005850024,0.0003502372,0.0008026293,0.00006996936],"domain_scores_gemma":[0.9943503,0.00186088,0.001803549,0.0001152178,0.001653386,0.0002168611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001061765,0.0002100799,0.003642864,0.1903333,0.006043924,0.0003263086,0.0001216652,0.0006130379,0.0008702429,0.002744281,0.114751,0.6792815],"study_design_scores_gemma":[0.001312088,0.001088593,0.01543871,0.4837294,0.01757349,0.003588475,0.000463327,0.0009378074,0.0008992979,0.01151311,0.4632803,0.0001756317],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.000199091,0.9882621,0.0002995578,0.009334674,0.001291545,0.00004424314,0.0000890989,0.00001640813,0.0004631976],"genre_scores_gemma":[0.007897192,0.9685708,0.002931044,0.01523036,0.004101401,0.000130097,0.0001678869,0.0000120162,0.0009591484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004419283,"threshold_uncertainty_score":0.0233717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02519681472693461,"score_gpt":0.2273942831369598,"score_spread":0.2021974684100251,"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."}}