{"id":"W4403226978","doi":"10.1016/j.cjca.2024.08.049","title":"CHARACTERIZATION OF PATIENTS SUB-OPTIMALLY TREATED FOR DYSLIPIDEMIA MANAGEMENT IN SECONDARY PREVENTION FOLLOWING THE PUBLICATION OF THE 2021 CCS DYSLIPIDEMIA GUIDELINES","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Lipoproteins and Cardiovascular Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine; Dyslipidemia; Secondary prevention; Characterization (materials science); Intensive care medicine; Primary prevention; Internal medicine; Nanotechnology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007790839,0.0001710048,0.0005898066,0.0008930856,0.0006742904,0.001271487,0.00039934,0.0009220691,0.001898165],"category_scores_gemma":[0.004795914,0.0001404951,0.000598294,0.001045494,0.0001942861,0.0005797217,0.0004779538,0.001380268,0.0004914538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007850302,"about_ca_system_score_gemma":0.00224141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006919991,"about_ca_topic_score_gemma":0.01221701,"domain_scores_codex":[0.9990118,0.0001832892,0.0002127772,0.0001333609,0.0002062046,0.00025265],"domain_scores_gemma":[0.9976892,0.0003830752,0.000828873,0.00007848027,0.0004784466,0.0005418372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007839932,0.0002195887,0.982502,0.00005109046,0.00006146047,0.0005294455,0.0002138838,0.00008767316,0.0003662898,0.0002795797,0.002288876,0.01261616],"study_design_scores_gemma":[0.00004115361,0.0003657722,0.9924377,0.0001983759,0.0001248972,0.001017035,0.0008723586,0.0005602953,0.0002604208,0.00050249,0.00359556,0.0000238846],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802669,0.002560257,0.0007063829,0.003775074,0.0002061474,0.0001582368,0.002106226,0.00002416675,0.01019669],"genre_scores_gemma":[0.9938594,0.0009190078,0.0008104246,0.00157587,0.0002024686,0.0001018509,0.0015282,0.00001629486,0.0009866013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006919991,"threshold_uncertainty_score":0.01375937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02062545676217562,"score_gpt":0.2804347937864585,"score_spread":0.2598093370242828,"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."}}