{"id":"W3152713532","doi":"10.1002/lt.26078","title":"Applying Administrative Data‐Based Coding Algorithms for Frailty in Patients With Cirrhosis","year":2021,"lang":"en","type":"article","venue":"Liver Transplantation","topic":"Frailty in Older Adults","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Allergan; National Institutes of Health; National Institute of Diabetes and Digestive and Kidney Diseases; Bausch Health; Gilead Sciences","keywords":"Medicine; Receiver operating characteristic; Liver transplantation; Cirrhosis; Hazard ratio; Frailty Index; Prospective cohort study; Activities of daily living; Physical therapy; Internal medicine; Transplantation; Confidence interval","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008343995,0.0001310571,0.0001910943,0.00007282509,0.00005640552,0.00002114752,0.00008001355,0.00006863149,0.00004768537],"category_scores_gemma":[0.00003221421,0.0001235899,0.00002874213,0.0001963679,0.00002909371,0.0002286539,0.000006342674,0.0001207528,0.000005139165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005481882,"about_ca_system_score_gemma":0.0001505053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005489478,"about_ca_topic_score_gemma":0.00032557,"domain_scores_codex":[0.9989384,0.00003430034,0.0002080529,0.00037537,0.0002574839,0.0001864377],"domain_scores_gemma":[0.9992571,0.0002016136,0.00005858644,0.0002667626,0.0001507271,0.00006514405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008909021,0.002837449,0.8547902,0.006879381,0.0005505515,0.001532916,0.009528561,0.0004024004,0.003665332,0.0003765227,0.0006682355,0.1098595],"study_design_scores_gemma":[0.01819185,0.0007408458,0.9400294,0.001300585,0.0005211937,0.00002889683,0.0003924398,0.01546913,0.02231557,0.00002199695,0.0006439064,0.0003441463],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7814268,0.00009196258,0.21118,0.0005930279,0.0002408943,0.003324456,0.002181655,0.0001080563,0.0008531808],"genre_scores_gemma":[0.9565536,0.00004113493,0.03278697,0.0003368431,0.00004201264,0.0002098231,0.009937969,0.00002222768,0.00006945444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.178393,"threshold_uncertainty_score":0.5039848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0892176071849211,"score_gpt":0.3292046836127829,"score_spread":0.2399870764278618,"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."}}