{"id":"W4382182054","doi":"10.1148/radiol.231066","title":"Reliability of LI-RADS for MRI and CT: Is Excellence Achievable?","year":2023,"lang":"en","type":"letter","venue":"Radiology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Medicine; Excellence; Nuclear medicine; Medical physics; Magnetic resonance imaging; Radiology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007690283,0.0002699389,0.001052131,0.0001835558,0.00006636012,0.000007803139,0.0002049216,0.0004957663,0.00007050316],"category_scores_gemma":[0.001412423,0.0002216534,0.0002022758,0.0001229924,0.0005647375,0.00002299626,0.00008669271,0.001786005,0.00001459884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005376363,"about_ca_system_score_gemma":0.0001345206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001036743,"about_ca_topic_score_gemma":5.564289e-7,"domain_scores_codex":[0.9980711,0.0001270907,0.0004935849,0.0006514487,0.0001947845,0.0004619292],"domain_scores_gemma":[0.9979652,0.001044503,0.0002274779,0.0005629376,0.00009494467,0.0001049994],"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":[0.00005192529,0.00001797173,0.004291099,0.001694646,0.0000972347,0.0001957322,0.0001292367,0.000008016305,0.0002662714,0.0000340249,0.9906675,0.002546297],"study_design_scores_gemma":[0.001036006,0.0004688156,0.002861015,0.0002985034,0.0002595578,0.0006541565,0.00001292025,0.005519625,0.00004890297,0.001528343,0.987095,0.0002171778],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.02253144,0.001473134,0.002792399,0.9700997,0.001375556,0.0008124031,0.00008505748,0.0001167092,0.0007136176],"genre_scores_gemma":[0.02332573,0.004757069,0.01075217,0.9282831,0.00890096,0.0001995655,0.0006917033,0.0002755773,0.0228141],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.04181657,"threshold_uncertainty_score":0.9038762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01529284050044762,"score_gpt":0.2982801387123396,"score_spread":0.282987298211892,"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."}}