{"id":"W4385405616","doi":"10.1093/clinchem/hvad112","title":"Short Timeframe Prediction of Kidney Failure among Patients with Advanced Chronic Kidney Disease","year":2023,"lang":"en","type":"article","venue":"Clinical Chemistry","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Queen's University; Ottawa Hospital; University of Ottawa; Canadian Electricity Association; Sunnybrook Health Science Centre; Carleton University","funders":"Canadian Institutes of Health Research","keywords":"Receiver operating characteristic; Medicine; Kidney disease; Proportional hazards model; Random forest; Renal function; Internal medicine; Dialysis; Survival analysis; Machine learning; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003328132,0.0004245744,0.0004090854,0.0007602927,0.0002442221,0.0005994147,0.0003757644,0.0004450593,0.0006721363],"category_scores_gemma":[0.008115591,0.0001639292,0.0007007725,0.0006420004,0.0001701288,0.0005869105,0.0004326301,0.0007451309,0.0001598508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003491108,"about_ca_system_score_gemma":0.0005905182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003879129,"about_ca_topic_score_gemma":0.005032923,"domain_scores_codex":[0.9991166,0.0003309264,0.00009152821,0.0001820978,0.000172785,0.0001060872],"domain_scores_gemma":[0.9947346,0.002317799,0.001802174,0.000291283,0.0005310965,0.0003229385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001991242,0.00003672736,0.9960651,0.00001209997,0.00005373623,0.00001744219,0.00002368719,0.0009048135,0.00006660334,0.00001696594,0.0001221916,0.002481654],"study_design_scores_gemma":[0.00001985248,0.0006485895,0.9788802,0.00003073777,0.0001182179,0.0002450088,0.0001073086,0.01911722,0.0002836911,0.0001855396,0.000351616,0.00001199012],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974647,0.0003535135,0.001344139,0.00008281819,0.00001366966,0.00001436554,0.0005214707,0.00001728549,0.000187978],"genre_scores_gemma":[0.9988402,0.00006624337,0.000551986,0.00001156838,0.00001243223,0.000008511939,0.0004540233,0.000002059296,0.00005316508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003879129,"threshold_uncertainty_score":0.01760101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215142546474426,"score_gpt":0.2853245382355027,"score_spread":0.2731731127707585,"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."}}