{"id":"W2160963614","doi":"10.1001/archinternmed.2009.328","title":"Evaluating the Incremental Benefits of Raising High-Density Lipoprotein Cholesterol Levels During Lipid Therapy After Adjustment for the Reductions in Other Blood Lipid Levels","year":2009,"lang":"en","type":"article","venue":"Archives of Internal Medicine","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Clinical Research Institute; McGill University Health Centre","funders":"","keywords":"Cholesterol; Hazard ratio; Internal medicine; Medicine; Confidence interval; High-density lipoprotein; Confounding; Blood lipids; Risk factor; Lipid profile; Lipoprotein; Endocrinology; Proportional hazards model","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":[0.006222752,0.0005993667,0.0005872009,0.0004411476,0.0001518098,0.00063461,0.0005965812,0.0006944428,0.001540591],"category_scores_gemma":[0.01447172,0.0001930894,0.002213493,0.0005513692,0.0002232141,0.0005283993,0.0003447679,0.0009560634,0.000136702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004458483,"about_ca_system_score_gemma":0.0007772001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002266542,"about_ca_topic_score_gemma":0.002030917,"domain_scores_codex":[0.9982034,0.001174771,0.00009585812,0.0001808989,0.0002071586,0.0001378397],"domain_scores_gemma":[0.9882463,0.009260554,0.001209042,0.0004971168,0.0003585402,0.000428453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03300452,0.0007299635,0.9223202,0.0002601251,0.005428512,0.0001757032,0.00006795141,0.0046341,0.001497526,0.0001436471,0.0003026883,0.03143508],"study_design_scores_gemma":[0.0009951459,0.01009925,0.9665143,0.00003594419,0.006354215,0.0002306204,0.00007074919,0.01293613,0.001772184,0.0003260735,0.0006367521,0.00002858226],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968835,0.001258038,0.0008457071,0.0002149718,0.0000366529,0.00003538364,0.0003386167,0.00001738331,0.0003698135],"genre_scores_gemma":[0.9984903,0.0002403097,0.0006616415,0.00005797093,0.00004240694,0.00002262439,0.0003213314,0.000003672951,0.0001596889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006222752,"threshold_uncertainty_score":0.03290945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05417387185911415,"score_gpt":0.3230361137674237,"score_spread":0.2688622419083096,"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."}}