{"id":"W4403227584","doi":"10.1016/j.cjca.2024.08.054","title":"OPTIMIZING SECONDARY PREVENTION USING A NOVEL MULTIDISCIPLINARY RISK REDUCTION CLINIC: INSIGHTS FROM A METROPOLITAN COMMUNITY CARDIOLOGY CLINIC","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Hospital Edmonton","funders":"","keywords":"Medicine; Multidisciplinary approach; Metropolitan area; Reduction (mathematics); Secondary prevention; Internal medicine; Cardiology; Intensive care medicine; Pathology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002370866,0.0003536305,0.0003035262,0.0006742647,0.008032264,0.003779395,0.001892355,0.002087184,0.006155964],"category_scores_gemma":[0.005545345,0.0004821681,0.0003741379,0.0008354289,0.001753283,0.001237027,0.002779887,0.002920995,0.000422744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006656608,"about_ca_system_score_gemma":0.02026755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09612916,"about_ca_topic_score_gemma":0.3219245,"domain_scores_codex":[0.9968807,0.001480463,0.00007996101,0.0002817135,0.0003945242,0.0008826365],"domain_scores_gemma":[0.9905611,0.00170788,0.000713461,0.0002638907,0.001115963,0.005637639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001146394,0.03138348,0.6086088,0.0004359975,0.0003217526,0.02016592,0.07688551,0.001935139,0.005609542,0.008551478,0.04653439,0.1984216],"study_design_scores_gemma":[0.001003074,0.006562707,0.6373072,0.0009415388,0.000343771,0.007169736,0.289617,0.008181554,0.001283106,0.007169907,0.04015703,0.0002633867],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9628173,0.0003364641,0.001033964,0.02470933,0.0001261005,0.0002297779,0.0001374885,0.00003568384,0.01057389],"genre_scores_gemma":[0.9871552,0.0006033169,0.003516139,0.006249168,0.0002095195,0.00011733,0.00009791759,0.00003304449,0.00201838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09612916,"threshold_uncertainty_score":0.1911393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4766065821528551,"score_gpt":0.5918980557265977,"score_spread":0.1152914735737426,"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."}}