{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01326884,0.0003562423,0.000762089,0.001907667,0.0006081405,0.001771318,0.0009279047,0.0009732688,0.001339377],"category_scores_gemma":[0.04775689,0.0004302695,0.00192514,0.005016504,0.0006788028,0.001416699,0.001414718,0.001554654,0.0003063935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008940137,"about_ca_system_score_gemma":0.001405091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01180688,"about_ca_topic_score_gemma":0.008428306,"domain_scores_codex":[0.9846187,0.006577399,0.002646484,0.002526205,0.002936051,0.0006951425],"domain_scores_gemma":[0.9217845,0.036838,0.0269447,0.008840196,0.004236279,0.001356382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002295649,0.0001142268,0.9969149,0.00008348397,0.0004478879,0.00004094163,0.0001063934,0.0002384671,0.00003841063,0.00007868995,0.0004214475,0.001285617],"study_design_scores_gemma":[0.00005015566,0.0002307904,0.9940953,0.00007974657,0.0003405986,0.0003900231,0.000528153,0.002701346,0.0001523241,0.0001822804,0.001227368,0.0000218594],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861807,0.001199044,0.001879635,0.0003059959,0.00004243905,0.0000838034,0.009716462,0.0000198915,0.0005720258],"genre_scores_gemma":[0.9924731,0.0002494605,0.001041889,0.0001162906,0.00003481134,0.0000733808,0.005938066,0.000007472637,0.00006554229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01326884,"threshold_uncertainty_score":0.0701732,"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."}}