{"id":"W2107006699","doi":"10.1016/j.jcrc.2015.08.019","title":"Whole-blood neutrophil gelatinase-associated lipocalin to predict adverse events in acute kidney injury: A prospective observational cohort study","year":2015,"lang":"en","type":"article","venue":"Journal of Critical Care","topic":"Acute Kidney Injury Research","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; Kingston General Hospital; Queen's University; Mount Sinai Hospital; Health Sciences Centre; Sunnybrook Health Science Centre; St. Michael's Hospital; Muscular Dystrophy Canada; University of Toronto","funders":"Canada Research Chairs; Alberta Innovates; Alere","keywords":"Medicine; Acute kidney injury; Renal replacement therapy; Internal medicine; Odds ratio; Confidence interval; Lipocalin; Prospective cohort study; Population; Cohort study; Intensive care unit; Area under the curve; Intensive care; Intensive care medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001327741,0.0002570774,0.0007725778,0.0004310769,0.00007178801,0.00001793476,0.000294229,0.000193857,0.0000911344],"category_scores_gemma":[0.01460254,0.0002180048,0.0001872701,0.0008239754,0.0001095324,0.0003808557,0.0001739669,0.001212986,0.00004366329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001130625,"about_ca_system_score_gemma":0.002124859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003427836,"about_ca_topic_score_gemma":0.000008647882,"domain_scores_codex":[0.9954969,0.0003857935,0.0009478853,0.000347776,0.002286267,0.0005353368],"domain_scores_gemma":[0.9935055,0.0001534057,0.000156135,0.0002972406,0.003902989,0.001984692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00293488,0.002542602,0.9776131,0.00006902954,0.0003470457,0.00151279,0.001889077,0.000003674659,0.0007323893,0.0000536184,0.01227697,0.0000248441],"study_design_scores_gemma":[0.009717648,0.01207813,0.9722633,0.0002813534,0.001067424,0.0001564374,0.003159528,0.00006337764,0.0003165417,0.0003445513,0.0003473528,0.000204387],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9849118,0.00003565502,0.00002964504,0.01179613,0.0003436012,0.001545695,0.0006830005,0.00002764425,0.0006268147],"genre_scores_gemma":[0.9967638,0.000001636903,0.0007297787,0.001608499,0.0004049342,0.00009487006,0.00009635997,0.00004497085,0.0002551038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0132748,"threshold_uncertainty_score":0.9936979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04795302731423191,"score_gpt":0.3853167777217579,"score_spread":0.337363750407526,"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."}}