{"id":"W4280619993","doi":"10.1016/j.ekir.2022.05.004","title":"Development and External Validation of a Machine Learning Model for Progression of CKD","year":2022,"lang":"en","type":"article","venue":"Kidney International Reports","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Manitoba; Ottawa Hospital; Seven Oaks General Hospital","funders":"Alberta Health Services","keywords":"Medicine; Kidney disease; Renal function; Albuminuria; Receiver operating characteristic; Creatinine; Confidence interval; Population; Internal medicine; Area under the curve; Urine; Demographics; Cohort; External validity; Urology; Demography; Statistics; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000285343,0.00006384756,0.0001379404,0.0001003638,0.0000544215,0.000004455201,0.00003512117,0.00001698291,0.0001896394],"category_scores_gemma":[0.000575805,0.00005938187,0.00005452771,0.00003956986,0.00002023602,0.00004582221,0.00008854263,0.000066049,1.605558e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007940536,"about_ca_system_score_gemma":0.0005402254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006042027,"about_ca_topic_score_gemma":1.934473e-7,"domain_scores_codex":[0.9989689,0.0000101777,0.0003749479,0.0001528071,0.0004176561,0.00007553833],"domain_scores_gemma":[0.9993095,0.00002478913,0.0003298317,0.00007773477,0.0001371865,0.0001209521],"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":[0.001625136,0.001809227,0.6939244,0.00128038,0.0006748196,0.0001779089,0.003705742,0.005364,0.2243585,0.001761142,0.005322766,0.05999602],"study_design_scores_gemma":[0.004921583,0.000596363,0.01357446,0.000886525,0.0002723263,0.0005517302,0.0002319618,0.5173329,0.3912769,0.003189525,0.06684056,0.000325168],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948044,0.0002260465,0.003181446,0.0004022176,0.0001506656,0.0002964431,0.00004823251,0.00001620591,0.0008743592],"genre_scores_gemma":[0.9863317,0.000007526609,0.01192626,0.0001251889,0.0000284426,0.00009288224,0.0004701358,0.000009944924,0.001007916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6803499,"threshold_uncertainty_score":0.2421522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02081007202334375,"score_gpt":0.3080668728318812,"score_spread":0.2872568008085374,"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."}}