{"id":"W2729845490","doi":"10.1186/s12882-017-0629-z","title":"Urinalysis findings and urinary kidney injury biomarker concentrations","year":2017,"lang":"en","type":"article","venue":"BMC Nephrology","topic":"Acute Kidney Injury Research","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"BioFrontiers Institute, University of Colorado Boulder; National Center for Advancing Translational Sciences; Yale University; National Institutes of Health; Ontario Ministry of Health and Long-Term Care; Raymond and Beverly Sackler Institute for Biological, Physical and Engineering Sciences, Yale University; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; Institute for Clinical Evaluative Sciences","keywords":"Urinalysis; Medicine; Urinary system; Proteinuria; Biomarker; Pyuria; Dipstick; Nephrology; Acute kidney injury; Urine; Urology; Internal medicine; Lipocalin; Leukocyte esterase; Creatinine; Gastroenterology; Kidney","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":[0.0007226614,0.0003079835,0.0006463132,0.0007370643,0.0002988521,0.0006761649,0.0002757086,0.0003098781,0.001072269],"category_scores_gemma":[0.004366358,0.0002596118,0.0003449224,0.0008476986,0.0003579275,0.0004302586,0.0004433723,0.0006692271,0.0001817582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002243655,"about_ca_system_score_gemma":0.0002766786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001504901,"about_ca_topic_score_gemma":0.001957148,"domain_scores_codex":[0.9992037,0.0001801651,0.0001434857,0.0001554353,0.0001953456,0.000121824],"domain_scores_gemma":[0.9972125,0.0006703805,0.001367746,0.0001668051,0.0002928014,0.0002897212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00015306,0.00003028515,0.9979716,0.00001793193,0.00004421939,0.0001194022,0.00005188925,0.00003270654,0.0006249236,0.000007876438,0.00003359763,0.0009126134],"study_design_scores_gemma":[0.000003772906,0.0001935133,0.9986632,0.000005124066,0.00002324716,0.0004525442,0.00006165888,0.0001437573,0.0003516519,0.00001115674,0.00008652473,0.00000374397],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998843,0.0003942513,0.0001950839,0.0000217083,0.000005243738,0.00001244575,0.0002085278,0.000006454535,0.0003132204],"genre_scores_gemma":[0.9992756,0.000111663,0.0002213943,0.00001796989,0.000006465182,0.00001011839,0.0001707402,0.00000242271,0.0001835181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001504901,"threshold_uncertainty_score":0.00382185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04711209957898444,"score_gpt":0.3618187402300825,"score_spread":0.3147066406510981,"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."}}