{"id":"W4416792092","doi":"10.1002/jmri.70192","title":"Prospective Comparison of <scp>DWI</scp> ‐Derived Virtual <scp>MR</scp> Elastography and Conventional <scp>MR</scp> Elastography in Metabolic Dysfunction‐Associated Steatotic Liver Disease and Healthy Volunteers","year":2025,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Heart Institute; McGill University Health Centre; Centre Hospitalier de l’Université de Montréal; McGill University; Philips (Canada); Université de Montréal; CARE Canada","funders":"Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Fondation de l'Association des radiologistes du Québec; Institute of Nutrition, Metabolism and Diabetes; Siemens Healthineers","keywords":"Elastography; Transient elastography; Magnetic resonance elastography; Fatty liver; Prospective cohort study; Ultrasound elastography; Stage (stratigraphy); Liver disease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002145707,0.000433758,0.0002834674,0.0003675508,0.000317745,0.0003741616,0.0001912281,0.0004727902,0.0008015927],"category_scores_gemma":[0.00488193,0.0003992032,0.0001948473,0.0002022634,0.000418574,0.0004242991,0.000371709,0.0003118342,0.000288955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001143274,"about_ca_system_score_gemma":0.0001174513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005303965,"about_ca_topic_score_gemma":0.0007045198,"domain_scores_codex":[0.9992999,0.0003135385,0.00005695152,0.0002040135,0.00007322651,0.00005239285],"domain_scores_gemma":[0.9973628,0.00107032,0.0005514966,0.0002967452,0.0004150172,0.0003035023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003815491,0.0003305758,0.985394,0.00003827886,0.0001574219,0.0001501704,0.0004451793,0.0001359637,0.005634712,0.0000409463,0.0001004495,0.003756835],"study_design_scores_gemma":[0.00008115851,0.002819759,0.994578,0.000004768804,0.00006686564,0.0003257887,0.0001795179,0.000590637,0.001188624,0.00002533254,0.0001303423,0.000009178777],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996657,0.00004014609,0.0001795574,0.000003297117,0.000002153669,0.00001230796,0.00003466408,0.000002787978,0.00005933292],"genre_scores_gemma":[0.9996961,0.000008598539,0.0001662112,0.000004514196,0.000002978765,0.00001235512,0.00005834034,0.000001404089,0.0000495659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002145707,"threshold_uncertainty_score":0.01134771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007927029105133878,"score_gpt":0.2548381828562709,"score_spread":0.246911153751137,"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."}}