{"id":"W4387933790","doi":"10.1016/j.jcjd.2023.10.293","title":"DEVELOPMENT AND INTERNAL VALIDATION OF THE CORONARY REVASCULARIZATION-TOOL FOR EVIDENCE-BASED INDIVIDUALIZED SHARED DECISION-MAKING (CR-DECIDE) QUALITY OF LIFE PREDICTION MODEL","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Diabetes","topic":"Heart Rate Variability and Autonomic Control","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine; Coronary artery disease; Revascularization; CAD; Coronary angiography; Clinical decision making; Intensive care medicine; Quality of life (healthcare); Quality (philosophy); Point of care; Relevance (law); Clinical judgment; Coronary disease; Internal medicine; Cardiology; Coronary heart disease; Medical physics; Pathology; Myocardial infarction; Nursing","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":[0.03023548,0.001056964,0.001411616,0.001646255,0.000638229,0.00252982,0.00145871,0.001084541,0.002669375],"category_scores_gemma":[0.07802639,0.000541057,0.001947029,0.001209204,0.0005589278,0.0009635197,0.002821422,0.002083884,0.0007921876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001134901,"about_ca_system_score_gemma":0.003545036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003320572,"about_ca_topic_score_gemma":0.003019344,"domain_scores_codex":[0.9864427,0.007145803,0.001597516,0.001754683,0.002660667,0.0003986844],"domain_scores_gemma":[0.9548129,0.03220447,0.002431369,0.002739696,0.007251637,0.0005598814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004593309,0.002839183,0.5176012,0.0007419467,0.003576545,0.0002229893,0.00104504,0.06211124,0.002217164,0.007118292,0.01536166,0.3825715],"study_design_scores_gemma":[0.001947567,0.002262581,0.2103873,0.0006705439,0.001710367,0.0005620013,0.0005308234,0.7523526,0.008152745,0.009959986,0.01128031,0.0001831999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6974046,0.0006296806,0.2761324,0.001506798,0.0003619802,0.005053824,0.009052941,0.003196439,0.006661341],"genre_scores_gemma":[0.831243,0.0001158257,0.1573872,0.0002737249,0.00004692989,0.004102854,0.005965921,0.0001634399,0.0007011408],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03023548,"threshold_uncertainty_score":0.1599025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06072470984865789,"score_gpt":0.3018170479881608,"score_spread":0.241092338139503,"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."}}