{"id":"W2752535395","doi":"10.1097/rmr.0000000000000149","title":"Liver Fibrosis Quantification by Magnetic Resonance Imaging","year":2017,"lang":"en","type":"review","venue":"Topics in Magnetic Resonance Imaging","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"CARE Canada; Canadian Institutes of Health Research; Centre Hospitalier de l’Université de Montréal; Philips (Canada); Institute of Nutrition, Metabolism and Diabetes; Université de Montréal","funders":"Institute of Nutrition, Metabolism and Diabetes; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"Magnetic resonance imaging; Elastography; Medicine; Magnetic resonance elastography; Fibrosis; Radiology; Chronic liver disease; Liver biopsy; Hepatic fibrosis; Liver disease; Cirrhosis; Ultrasound; Pathology; Biopsy; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003592996,0.0007999396,0.001871975,0.0003642438,0.0002440527,0.0002945407,0.0006592824,0.0001907956,0.0004435865],"category_scores_gemma":[0.0002326927,0.0007257059,0.0005351762,0.0003358893,0.000315088,0.0002420924,0.0002274719,0.0006355969,0.0002572162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004925181,"about_ca_system_score_gemma":0.0003731482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005053299,"about_ca_topic_score_gemma":0.00002103377,"domain_scores_codex":[0.9959342,0.0002022963,0.001104539,0.001344314,0.000605402,0.0008092472],"domain_scores_gemma":[0.9970091,0.0002165736,0.0004683201,0.001919314,0.0001413242,0.0002453834],"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":[0.00001676834,0.0002836899,0.01300522,0.003573307,0.000008046426,0.0005007001,0.00006798813,4.610136e-8,7.750303e-7,0.0001700427,0.008099901,0.9742735],"study_design_scores_gemma":[0.001024288,0.00007634616,0.03160959,0.02200008,0.0008199649,0.00008964526,0.00001460533,0.0002977279,0.000003967045,0.00007098092,0.9433954,0.0005973497],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003571353,0.9922336,0.000009221269,0.0006534384,0.0003839223,0.001840401,0.0001849179,0.00008561125,0.004573178],"genre_scores_gemma":[0.0001475762,0.9900719,0.001034533,0.0002295074,0.0003772926,0.0007269427,0.0002934738,0.0001266622,0.006992114],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9736761,"threshold_uncertainty_score":0.9995194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04870972956068827,"score_gpt":0.3443038531492177,"score_spread":0.2955941235885295,"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."}}