{"id":"W3211721508","doi":"10.2196/31356","title":"Real-world Health Data and Precision for the Diagnosis of Acute Kidney Injury, Acute-on-Chronic Kidney Disease, and Chronic Kidney Disease: Observational Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Kidney disease; Acute kidney injury; Medical diagnosis; Diagnosis code; Observational study; Medical record; Intensive care medicine; Retrospective cohort study; Creatinine; Disease; Emergency medicine; Internal medicine; Pathology; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008741124,0.0004014443,0.0007927998,0.0001623317,0.0003378258,0.0000996028,0.000548223,0.0001204142,0.0006235738],"category_scores_gemma":[0.004113057,0.0002787941,0.0001535541,0.0005198139,0.0004035791,0.0004908014,0.0009084961,0.0004277876,0.00001032672],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003527713,"about_ca_system_score_gemma":0.01804808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002527905,"about_ca_topic_score_gemma":0.00001798388,"domain_scores_codex":[0.9958357,0.0001166106,0.0013383,0.0004763872,0.001630985,0.0006020286],"domain_scores_gemma":[0.9912047,0.0009741545,0.0004428348,0.001639469,0.0002574475,0.005481441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009716081,0.001764649,0.1125103,0.005682141,0.001770778,0.00004182078,0.001020312,0.000001384764,0.000009876602,0.0008108758,0.8487602,0.02665597],"study_design_scores_gemma":[0.02828604,0.005294972,0.3745342,0.01146693,0.007228389,0.00002340608,0.001079812,0.1285381,0.0001814147,0.001028396,0.4411594,0.001179],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6029027,0.01156972,0.001355161,0.2617316,0.002064997,0.02175083,0.09723121,0.0004962233,0.0008975352],"genre_scores_gemma":[0.7280501,0.07019476,0.002646896,0.1252664,0.003325483,0.004606722,0.06366593,0.0002609437,0.001982775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4076008,"threshold_uncertainty_score":0.9999664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05565987773002401,"score_gpt":0.3863199458435256,"score_spread":0.3306600681135016,"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."}}