{"id":"W4387338165","doi":"10.1016/j.cjca.2023.06.290","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 Cardiology","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine; Coronary artery disease; Revascularization; CAD; Coronary angiography; Clinical decision making; Quality of life (healthcare); Intensive care medicine; Internal medicine; Point of care; Quality (philosophy); Relevance (law); Cardiology; Clinical judgment; Medical physics; Myocardial infarction; Pathology; 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":[0.03397525,0.0009836855,0.001272166,0.001863519,0.0005787712,0.002476683,0.00159574,0.001218982,0.003544177],"category_scores_gemma":[0.1086743,0.0005341751,0.00196242,0.001367294,0.0005885241,0.001102453,0.00315402,0.002109202,0.001012753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001327473,"about_ca_system_score_gemma":0.004013245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003746166,"about_ca_topic_score_gemma":0.002927951,"domain_scores_codex":[0.9829189,0.009443748,0.001891169,0.00201853,0.003285123,0.0004425463],"domain_scores_gemma":[0.9332827,0.04875433,0.003488783,0.004037983,0.009700819,0.0007353848],"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":[0.00454006,0.003004737,0.4394624,0.0008787934,0.003255161,0.0002317313,0.001034985,0.09372323,0.001885571,0.01304835,0.02154974,0.4173853],"study_design_scores_gemma":[0.001701105,0.001654243,0.1440577,0.0006209394,0.001365548,0.0004172911,0.0003966262,0.8164521,0.006814037,0.0138556,0.01252232,0.0001424151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6456362,0.0006816471,0.3199791,0.001844269,0.0003553499,0.006070473,0.01180693,0.003746643,0.009879311],"genre_scores_gemma":[0.8123125,0.0001145305,0.1743383,0.0002778507,0.00004543693,0.004171206,0.007693849,0.0001822024,0.0008641959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03397525,"threshold_uncertainty_score":0.1796805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3593226452407013,"score_gpt":0.4084280527826635,"score_spread":0.04910540754196219,"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."}}