{"id":"W3202957538","doi":"10.1002/lt.26332","title":"The Toronto Postliver Transplantation Hepatocellular Carcinoma Recurrence Calculator: A Machine Learning Approach","year":2021,"lang":"en","type":"article","venue":"Liver Transplantation","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hamilton Health Sciences; Toronto General Hospital; University of Toronto; University Health Network","funders":"","keywords":"Medicine; Hepatocellular carcinoma; Calculator; Liver transplantation; Transplantation; Oncology; Internal medicine; Surgery; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001187617,0.0002101724,0.0002049476,0.00002485074,0.0003515352,0.00006016063,0.00007211526,0.00008497096,0.0001220374],"category_scores_gemma":[0.00000820336,0.0001583289,0.0001747529,0.0001215947,0.00004814245,0.0002156168,0.000006701714,0.000164763,0.00003466699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001474643,"about_ca_system_score_gemma":0.0001263913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001388171,"about_ca_topic_score_gemma":0.0004589645,"domain_scores_codex":[0.9985259,0.0001728244,0.0002557285,0.0003929634,0.0003874053,0.000265172],"domain_scores_gemma":[0.9992909,0.0001203168,0.0000688025,0.0002193127,0.0001440895,0.0001565471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002041905,0.001450797,0.9481713,0.002201171,0.0006872782,0.006239112,0.01398333,0.000174587,0.003504289,0.005340736,0.0001111879,0.01609428],"study_design_scores_gemma":[0.00549878,0.0003883509,0.935178,0.0002878598,0.003027767,0.001449631,0.000785791,0.02647028,0.02487944,0.0000515717,0.001527255,0.0004552146],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764427,0.01618685,0.002462293,0.0002052494,0.0001582758,0.0006049327,0.0001473335,0.00008810616,0.003704297],"genre_scores_gemma":[0.9695787,0.02670138,0.0006890507,0.0001199879,0.00007193984,0.00009202987,0.002395347,0.00002436709,0.0003271923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02629569,"threshold_uncertainty_score":0.6456466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01640200540607929,"score_gpt":0.238079631406905,"score_spread":0.2216776260008257,"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."}}