{"id":"W2899096630","doi":"10.1002/hep.30343","title":"Letter to Editor: Using Proper Methods to Identify Patients With Cirrhosis in Administrative Databases Is Crucial to Correctly Predict Outcomes","year":2018,"lang":"en","type":"letter","venue":"Hepatology","topic":"Liver Disease and Transplantation","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Cirrhosis; Decompensation; Hepatic encephalopathy; Ascites; Context (archaeology); Database; Intensive care medicine; Internal medicine; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001669303,0.0004571573,0.0009395475,0.0006064851,0.00007250797,0.00003276735,0.0002088006,0.000408386,0.0003149157],"category_scores_gemma":[0.00008906936,0.0003526431,0.0001046044,0.0003451025,0.00008353734,0.0001455244,0.00009343415,0.0006289325,0.0002231779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001848959,"about_ca_system_score_gemma":0.0003694256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008023576,"about_ca_topic_score_gemma":0.0003777823,"domain_scores_codex":[0.9971054,0.0003772658,0.0005176642,0.0009187555,0.0005165368,0.0005644242],"domain_scores_gemma":[0.9985417,0.000213529,0.0001319209,0.0005319788,0.0003099064,0.0002710396],"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":[0.000680606,0.00007746834,0.4335573,0.000169101,0.0002510367,0.0003745044,0.001061212,2.239123e-7,0.00003981816,3.134652e-7,0.5636606,0.0001277872],"study_design_scores_gemma":[0.002758797,0.002068126,0.2955998,0.001296893,0.002364629,0.00004349793,0.00005862699,0.00002633989,0.002373582,0.000005901005,0.692472,0.0009317232],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"commentary","genre_scores_codex":[0.7850093,0.00002386917,0.007857678,0.1905071,0.009423012,0.004380805,0.002464836,0.00009866913,0.0002346705],"genre_scores_gemma":[0.03777664,0.000003232864,0.02393309,0.9224629,0.01346709,0.0003660918,0.001600827,0.0001111524,0.0002789218],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.7472327,"threshold_uncertainty_score":0.9998925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07740793809068057,"score_gpt":0.4137303264591931,"score_spread":0.3363223883685125,"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."}}