{"id":"W4407953840","doi":"10.1016/j.cjco.2025.02.016","title":"Development and Validation of Models to Predict Major Adverse Cardiovascular Events in Chronic Kidney Disease","year":2025,"lang":"en","type":"article","venue":"CJC Open","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Ottawa Hospital; University of Ottawa; University of Manitoba; Orthopaedic Innovation Centre","funders":"Canadian Institutes of Health Research; Bayer Canada; Servier; Vetenskapsrådet; Government of Alberta; Kidney Foundation of Canada; Astellas Pharma; Hjärt-Lungfonden; University of Calgary; Alberta Health Services; AstraZeneca; Eli Lilly and Company; Roche; GlaxoSmithKline; Amgen","keywords":"Kidney disease; Medicine; Disease; Intensive care medicine; Adverse effect; Internal medicine; Cardiology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0264279,0.001810508,0.000844539,0.002040903,0.0007567659,0.001821891,0.001953101,0.0008457325,0.0009195041],"category_scores_gemma":[0.03894638,0.0005739872,0.001826382,0.0009714225,0.0006333617,0.0009613906,0.001652411,0.001820099,0.0004074752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002042119,"about_ca_system_score_gemma":0.004746337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02930921,"about_ca_topic_score_gemma":0.02135458,"domain_scores_codex":[0.9946306,0.003335505,0.0003217345,0.0007265849,0.0007091859,0.0002764457],"domain_scores_gemma":[0.9749416,0.01715954,0.001640621,0.001206467,0.004613245,0.0004385831],"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":[0.0006702332,0.0007527168,0.5713754,0.0001681919,0.001611109,0.0001929683,0.0002560353,0.3547734,0.0006853604,0.00113877,0.004029893,0.06434593],"study_design_scores_gemma":[0.000107022,0.0003966418,0.04077137,0.0001122115,0.000245861,0.0000935488,0.00008736963,0.9548119,0.0007178849,0.001647184,0.0009821858,0.00002678159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8615139,0.0009784505,0.1285891,0.001005919,0.0002136203,0.0008822076,0.002685306,0.001020491,0.003111018],"genre_scores_gemma":[0.9515934,0.0002570421,0.04456341,0.0001442331,0.00004290451,0.0003732421,0.002420238,0.00005243967,0.0005531839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02930921,"threshold_uncertainty_score":0.1397657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0191451175631604,"score_gpt":0.2794962482932776,"score_spread":0.2603511307301172,"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."}}