{"id":"W2998368831","doi":"10.1002/hep.31103","title":"Applying Machine Learning in Liver Disease and Transplantation: A Comprehensive Review","year":2020,"lang":"en","type":"review","venue":"Hepatology","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":205,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto General Hospital; University Health Network; Vector Institute","funders":"","keywords":"Hepatology; Liver transplantation; Medicine; Internal medicine; Liver disease; Transplantation; Disease; Artificial intelligence; Machine learning; Computer science; Intensive care medicine; Medical physics","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":[0.00003663544,0.0003204817,0.001983509,0.0001067807,0.00003921048,0.000006565551,0.00004994097,0.0001059808,0.0001492179],"category_scores_gemma":[0.00003457759,0.0002482893,0.0002699771,0.000180761,0.0000495285,0.00002486192,0.00003712411,0.0003583176,0.00009367244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006968206,"about_ca_system_score_gemma":0.0002429831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007425324,"about_ca_topic_score_gemma":0.00001585406,"domain_scores_codex":[0.9985666,0.0002707113,0.0004068828,0.0004548641,0.000113047,0.0001879177],"domain_scores_gemma":[0.9991701,0.0002241324,0.0001398213,0.0001501517,0.00002759007,0.0002882571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000365401,0.00009911412,0.008234576,0.22702,0.0002428302,0.01076626,0.00002971958,2.783294e-8,9.018712e-9,0.00006371673,0.0001342347,0.753373],"study_design_scores_gemma":[0.0006218375,0.00007515997,0.000847415,0.05514776,0.007072388,0.0005900066,0.000001663377,0.0000714894,2.327734e-8,0.000003819568,0.9353946,0.0001738502],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000204061,0.996648,0.000002318777,0.0004600275,0.00003733756,0.00260973,0.00008229299,0.00004205181,0.00009785614],"genre_scores_gemma":[0.0001277959,0.9955979,0.00005025974,0.001499795,0.00004282509,0.00159225,0.001037556,0.00003360333,0.00001803181],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9352604,"threshold_uncertainty_score":0.999997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06528630599131584,"score_gpt":0.3391322463895536,"score_spread":0.2738459403982377,"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."}}