{"id":"W3169898767","doi":"10.2139/ssrn.3705267","title":"Effective Detection of Compensated Cirrhosis Using Machine Learning","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Institute for Clinical Evaluative Sciences; McGill University; University of Toronto; University Health Network; Genome Canada; Toronto Liver Centre","funders":"","keywords":"Artificial intelligence; Computer science; Cirrhosis; Machine learning; Medicine; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006583579,0.0004522943,0.0006349189,0.002171149,0.0002951065,0.0008186958,0.0003606234,0.0007004401,0.001477698],"category_scores_gemma":[0.001930378,0.0001764653,0.0003685568,0.0005666726,0.0001563812,0.0005167412,0.0004584927,0.0005067632,0.0008168003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002213552,"about_ca_system_score_gemma":0.0004296355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001221181,"about_ca_topic_score_gemma":0.001785682,"domain_scores_codex":[0.9995916,0.0001057084,0.00003791417,0.00006323384,0.0001235016,0.00007813655],"domain_scores_gemma":[0.9991553,0.0003700005,0.0001006476,0.00005942333,0.0002462258,0.00006845351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00169954,0.0005692744,0.1407644,0.0002900619,0.0001677114,0.00102845,0.00007821076,0.009558396,0.0868516,0.001225973,0.008919649,0.7488469],"study_design_scores_gemma":[0.0001197767,0.0008416973,0.1257679,0.00009877582,0.0002064012,0.00400094,0.0002040964,0.7869864,0.06928767,0.004809196,0.007580877,0.00009618871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6339076,0.006761467,0.3458867,0.001486283,0.0005231521,0.0002586028,0.001431756,0.00296685,0.006777487],"genre_scores_gemma":[0.9409221,0.0006367863,0.05479459,0.0002069735,0.0002099109,0.00004397841,0.000825893,0.00004886059,0.002310843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002171149,"threshold_uncertainty_score":0.004943371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01218542599823035,"score_gpt":0.2498411460038291,"score_spread":0.2376557200055988,"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."}}