{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0208027,0.001324904,0.0007694854,0.001219135,0.0006384329,0.001434037,0.001424565,0.001094703,0.001451574],"category_scores_gemma":[0.02399123,0.0003070438,0.0009470089,0.000603238,0.0006538891,0.0006332718,0.001324749,0.001442007,0.0007399371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001776027,"about_ca_system_score_gemma":0.002960299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01709611,"about_ca_topic_score_gemma":0.01045598,"domain_scores_codex":[0.9957015,0.002495031,0.0002501952,0.0006131493,0.000686236,0.0002538493],"domain_scores_gemma":[0.9831965,0.009966509,0.0009377212,0.001153225,0.004431993,0.000313999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001295307,0.001218437,0.3857878,0.000178233,0.0008578883,0.0002615859,0.0002456344,0.4931234,0.003797865,0.001113693,0.005042078,0.1070781],"study_design_scores_gemma":[0.0001040773,0.0003617521,0.02692601,0.00006334488,0.0001070545,0.00009659244,0.00004360827,0.9676055,0.002799899,0.0007810104,0.001086923,0.00002423601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8501221,0.0004955618,0.1424417,0.0004995534,0.0001155166,0.0005208103,0.001678293,0.0009635225,0.003162906],"genre_scores_gemma":[0.9678648,0.00006244094,0.02831462,0.0001065439,0.00002596042,0.0002115011,0.002613548,0.00004799802,0.0007526219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0208027,"threshold_uncertainty_score":0.1100165,"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."}}