{"id":"W4200028946","doi":"10.37765/ajmc.2021.88807","title":"Medical costs for managing chronic kidney disease and related complications in patients with chronic kidney disease and type 2 diabetes","year":2021,"lang":"en","type":"article","venue":"The American Journal of Managed Care","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Medicine, University of Toronto; Canadian Institutes of Health Research; AstraZeneca; Bayer; University of Toronto; Diabetes Canada","keywords":"Medicine; Kidney disease; Dialysis; Internal medicine; Hyperkalemia; Myocardial infarction; Heart failure; Intensive care medicine; Stroke (engine); Diabetes mellitus; Atrial fibrillation; Type 2 diabetes; Emergency medicine; Endocrinology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001196921,0.0004509752,0.0003055108,0.001865037,0.0003124433,0.0009396327,0.0004969906,0.0004878448,0.001571138],"category_scores_gemma":[0.007592,0.0002672315,0.001780694,0.002314175,0.0002202165,0.0008902662,0.001113046,0.0007739412,0.0001594066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002338226,"about_ca_system_score_gemma":0.001538604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02896359,"about_ca_topic_score_gemma":0.03214523,"domain_scores_codex":[0.9984021,0.0005913465,0.0003001472,0.0001578338,0.000345008,0.0002035237],"domain_scores_gemma":[0.9964852,0.0004724388,0.002464209,0.00008122889,0.0002734602,0.0002235072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002216117,0.0001204102,0.9750409,0.0002465088,0.000753045,0.0001427751,0.00009021024,0.00569208,0.000068548,0.000700064,0.003564419,0.01335943],"study_design_scores_gemma":[0.00007556233,0.0001800273,0.9809954,0.0003784301,0.000511623,0.0006200654,0.00031686,0.01128423,0.0001215744,0.0005944158,0.004890543,0.00003114676],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9613501,0.00571873,0.001596289,0.002042052,0.00009987595,0.0001672687,0.02484588,0.00003875901,0.004141047],"genre_scores_gemma":[0.9869399,0.001810519,0.001347457,0.0002720502,0.00008288537,0.00009626734,0.008890068,0.000006927977,0.0005540477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02896359,"threshold_uncertainty_score":0.05759001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004916633316283419,"score_gpt":0.2415461997620855,"score_spread":0.2366295664458021,"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."}}