{"id":"W3165559161","doi":"10.1016/j.cca.2021.05.022","title":"Calculating estimated glomerular filtration rate without the race correction factor: Observations at a large academic medical system","year":2021,"lang":"en","type":"article","venue":"Clinica Chimica Acta","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Nutrition, Metabolism and Diabetes","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Diabetes Research Center, University of Washington; National Institutes of Health","keywords":"Renal function; Creatinine; Medicine; Urology; Internal medicine; Population; Nephrology; Kidney disease; Risk factor; Race (biology); Biology","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":[0.001954303,0.0005797028,0.0009677394,0.0009059475,0.001439573,0.001117735,0.00149059,0.0008923439,0.001304814],"category_scores_gemma":[0.007778438,0.0007070336,0.0008858817,0.003117082,0.0005785978,0.001350136,0.00116907,0.001480522,0.0007822682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001637813,"about_ca_system_score_gemma":0.003256417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1482742,"about_ca_topic_score_gemma":0.139756,"domain_scores_codex":[0.9967127,0.001229101,0.0002934579,0.0007003475,0.00064486,0.000419628],"domain_scores_gemma":[0.9926485,0.001737263,0.00195982,0.001270636,0.001422525,0.0009612746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001219745,0.0001259651,0.9967134,0.00001052147,0.00006712471,0.0001586862,0.0002361427,0.0003380833,0.0002614178,0.00002586593,0.0005179229,0.00142294],"study_design_scores_gemma":[0.00002368542,0.0001499199,0.9970357,0.000005124334,0.00005465289,0.0001672473,0.0005438559,0.001505999,0.0001830312,0.00003713175,0.0002801188,0.00001343969],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968289,0.00004343287,0.0006777717,0.00008399455,0.000005624827,0.00002990768,0.001960657,0.00002124122,0.0003485376],"genre_scores_gemma":[0.9962209,0.00005323858,0.001247149,0.00006091482,0.00001941056,0.00003319625,0.002044054,0.00002334128,0.0002979943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1482742,"threshold_uncertainty_score":0.2948223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06440018175430316,"score_gpt":0.3581890794935581,"score_spread":0.2937888977392549,"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."}}