{"id":"W2794560981","doi":"10.1016/j.kint.2018.01.009","title":"Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate","year":2018,"lang":"en","type":"article","venue":"Kidney International","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":199,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; Institute for Clinical Evaluative Sciences; Sunnybrook Hospital; University of Toronto; Provincial Health Services Authority","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Heart, Lung, and Blood Institute; National Institutes of Health; Astellas Pharma; Sanofi; Fresenius Medical Care North America; National Center for Advancing Translational Sciences; Tufts Medical Center; AstraZeneca; Eli Lilly and Company; GlaxoSmithKline; Karolinska Institutet; National Institute of Diabetes and Digestive and Kidney Diseases; Johns Hopkins University; Amgen; U.S. Department of Veterans Affairs","keywords":"Medicine; Renal function; Kidney disease; Creatinine; Internal medicine; Diabetes mellitus; Albuminuria; Blood pressure; Urology; Intensive care medicine; Endocrinology","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":[0.0007899412,0.000435334,0.000595606,0.001245169,0.0005039138,0.001153939,0.0004896218,0.0008620199,0.001908509],"category_scores_gemma":[0.005544338,0.0002654486,0.0006923183,0.001308709,0.0003037601,0.0008834666,0.0008489435,0.001297223,0.0003097054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004906981,"about_ca_system_score_gemma":0.0009046385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003609427,"about_ca_topic_score_gemma":0.005244496,"domain_scores_codex":[0.9994169,0.0001668198,0.00009168733,0.00008148962,0.00007148731,0.000171596],"domain_scores_gemma":[0.9949141,0.001442761,0.00189164,0.0001510417,0.000324475,0.001276019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001941593,0.00002420107,0.9985749,0.000004539725,0.00001881644,0.00006460337,0.0000144942,0.00008633426,0.00004324845,0.00002666409,0.00007366484,0.0008743874],"study_design_scores_gemma":[0.00001335154,0.0001901399,0.997113,0.00001792566,0.00005972322,0.0004549453,0.0002452754,0.001344486,0.0001001441,0.0002120907,0.0002371719,0.00001181827],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99714,0.0005757771,0.0002170334,0.0002292629,0.00004926629,0.000007056496,0.000294992,0.000009828173,0.001476788],"genre_scores_gemma":[0.999006,0.0001449544,0.0002166581,0.0000372512,0.00005341665,0.000003837261,0.0003837386,0.000003090438,0.0001509978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003609427,"threshold_uncertainty_score":0.007176816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01747092124664526,"score_gpt":0.306496179265078,"score_spread":0.2890252580184327,"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."}}