{"id":"W4417138348","doi":"10.3350/cmh.2025.1267","title":"Optimized MASH treatment eligibility cutoffs for MRE-measured liver stiffness and proton density fat fraction","year":2025,"lang":"en","type":"article","venue":"Clinical and Molecular Hepatology","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Sonic Incytes; National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; Siemens; Novo Nordisk; Intercept Pharmaceuticals; Madrigal Pharmaceuticals; Regeneron Pharmaceuticals; Gilead Sciences; Arrowhead Pharmaceuticals; Merck; Bristol-Myers Squibb; Eli Lilly and Company; AstraZeneca; National Heart, Lung, and Blood Institute; NGM Biopharmaceuticals; Pfizer; Inventiva Pharma; Galectin Therapeutics; National Institute of Diabetes and Digestive and Kidney Diseases; Amgen","keywords":"Stiffness; Proton; Fatty liver; Adipose tissue","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000158615,0.0001829518,0.0006511251,0.00004620343,0.00009399535,0.00001513187,0.0000291418,0.0002217883,0.00001218928],"category_scores_gemma":[0.0002711345,0.0001361515,0.0002132423,0.00005227311,0.0002174562,0.00002621868,0.00004962081,0.00009211151,0.000003326924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005866091,"about_ca_system_score_gemma":0.0001207719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000133262,"about_ca_topic_score_gemma":0.00002035156,"domain_scores_codex":[0.9986469,0.0001575228,0.0003614764,0.0005652943,0.00007547183,0.0001933581],"domain_scores_gemma":[0.9989895,0.0003280374,0.0000710895,0.0002756639,0.0001378521,0.0001978461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00495889,0.002808755,0.9192647,0.0003557093,0.0009848299,0.0002945689,0.00002985845,7.757546e-7,0.0003815173,0.001031771,0.0004227989,0.06946588],"study_design_scores_gemma":[0.02966016,0.002044047,0.9279655,0.0001615627,0.003796226,0.00005549685,0.00004038226,0.003100637,0.01378911,0.004063671,0.01499382,0.0003293423],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907246,0.002073275,0.002385939,0.001971351,0.0001618953,0.002505949,0.00001897476,0.00003987658,0.0001181375],"genre_scores_gemma":[0.9945398,0.001991656,0.001298462,0.001360572,0.00003665582,0.0006142704,0.00005828379,0.000009836199,0.00009046296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06913653,"threshold_uncertainty_score":0.5552098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04243640188193786,"score_gpt":0.3853938234743923,"score_spread":0.3429574215924544,"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."}}