{"id":"W4310370526","doi":"10.1148/rg.220066","title":"Universal Liver Imaging Lexicon: Imaging Atlas for Research and Clinical Practice","year":2022,"lang":"en","type":"article","venue":"Radiographics","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; University of Toronto","funders":"Department of Science and Technology of Sichuan Province; National Natural Science Foundation of China","keywords":"Medicine; Atlas (anatomy); Lexicon; Medical physics; Clinical Practice; Clinical imaging; Radiology; Artificial intelligence; Family medicine; Anatomy","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":[0.00357443,0.001223132,0.001329403,0.01754167,0.001122203,0.007081724,0.002924822,0.002738909,0.05633373],"category_scores_gemma":[0.02344836,0.0009236016,0.001347858,0.02107022,0.00154593,0.005998672,0.004327282,0.003006772,0.04584746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003984483,"about_ca_system_score_gemma":0.009860996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009421241,"about_ca_topic_score_gemma":0.01198984,"domain_scores_codex":[0.9963038,0.001007186,0.001228364,0.0003263721,0.0009532484,0.0001810795],"domain_scores_gemma":[0.9866133,0.004594673,0.001752509,0.001422884,0.004933076,0.0006834532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008908495,0.00002016891,0.000784831,0.002033223,0.00002412517,0.0003016822,0.0005241921,0.0005347027,0.0007613346,0.03902175,0.8291248,0.1267803],"study_design_scores_gemma":[0.0000132468,0.000009965356,0.0008170513,0.0005608484,0.00001326617,0.0007690078,0.000124465,0.0004044448,0.00017478,0.008160289,0.9889284,0.00002418649],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004810892,0.05933573,0.3443269,0.03065847,0.007780404,0.004917219,0.2300353,0.03699279,0.2811423],"genre_scores_gemma":[0.02779292,0.04278137,0.6114489,0.01682416,0.003652521,0.006124035,0.2164894,0.01237216,0.06251456],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05633373,"threshold_uncertainty_score":0.1884551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05836767890696545,"score_gpt":0.4268881700065081,"score_spread":0.3685204910995427,"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."}}