{"id":"W2743691476","doi":"10.1016/j.jacc.2017.06.030","title":"Biomarker-Based Risk Model to Predict Cardiovascular Mortality in Patients With Stable Coronary Disease","year":2017,"lang":"en","type":"article","venue":"Journal of the American College of Cardiology","topic":"IL-33, ST2, and ILC Pathways","field":"Immunology and Microbiology","cited_by":140,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian VIGOUR Centre; University of Alberta","funders":"NIH Clinical Center","keywords":"Medicine; Biomarker; Internal medicine; Proportional hazards model; Cohort; Cardiology; Natriuretic peptide; Prospective cohort study; Cohort study; Coronary artery disease; Heart failure","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":[0.001605769,0.001126013,0.001142626,0.001108943,0.0002951158,0.001270845,0.000800701,0.0007282509,0.001935948],"category_scores_gemma":[0.002599269,0.0002580027,0.00104022,0.0004664555,0.0001401077,0.00037672,0.0005949943,0.000980061,0.0005167124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006272984,"about_ca_system_score_gemma":0.001369253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004933105,"about_ca_topic_score_gemma":0.00378284,"domain_scores_codex":[0.9996635,0.0001334283,0.00002796736,0.00007320238,0.00004712295,0.00005478831],"domain_scores_gemma":[0.9993082,0.0003441538,0.00008830695,0.00003160728,0.0001514514,0.00007627549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005524082,0.002043532,0.5769111,0.0002172809,0.003069811,0.0008250163,0.0001153037,0.305862,0.003416879,0.002172263,0.008524907,0.09131781],"study_design_scores_gemma":[0.0001015875,0.0003749512,0.0281317,0.00003149188,0.0004349383,0.0001621879,0.0000439902,0.9682855,0.0004264915,0.001362736,0.0006188099,0.00002561061],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9247131,0.002455286,0.06279628,0.002119742,0.0004271391,0.0001656324,0.003958578,0.0007289527,0.002635246],"genre_scores_gemma":[0.9904065,0.0003092319,0.006271242,0.000137888,0.00008764644,0.00009728315,0.001636346,0.00001538101,0.001038658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004933105,"threshold_uncertainty_score":0.009808838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554791852605216,"score_gpt":0.2327717964852353,"score_spread":0.2172238779591831,"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."}}