{"id":"W2770764122","doi":"10.1148/rg.2017170098","title":"2017 Version of LI-RADS for CT and MR Imaging: An Update","year":2017,"lang":"en","type":"review","venue":"Radiographics","topic":"Hepatocellular Carcinoma Treatment and Prognosis","field":"Medicine","cited_by":233,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; University of Ottawa","funders":"","keywords":"Medicine; Radiology; Magnetic resonance imaging; Malignancy; Hepatocellular carcinoma; Medical physics; Categorization; Appropriateness criteria; Computed tomography; Pathology; Internal medicine; Artificial intelligence","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":[0.003844689,0.0009445831,0.001973242,0.01007392,0.00041603,0.003038443,0.002161988,0.002167965,0.01275384],"category_scores_gemma":[0.01092246,0.0007067362,0.001455709,0.008796753,0.001278071,0.003943402,0.001629803,0.004241895,0.0171112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002193635,"about_ca_system_score_gemma":0.005609428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00420698,"about_ca_topic_score_gemma":0.004305604,"domain_scores_codex":[0.9970815,0.0005345072,0.0009264523,0.0002165645,0.001111356,0.000129696],"domain_scores_gemma":[0.9933169,0.002167115,0.001206552,0.0003341406,0.002763217,0.0002122206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00006478577,0.00002733284,0.0003999796,0.01618753,0.0000835511,0.0002869582,0.0001131403,0.0001467778,0.0006091753,0.004396614,0.193471,0.7842131],"study_design_scores_gemma":[0.0000086832,0.00001278598,0.0004703531,0.004909474,0.00005245456,0.001414232,0.00002552183,0.00002199523,0.0001322019,0.0004227288,0.9925142,0.00001532871],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001564516,0.9851961,0.000651981,0.003921991,0.002911774,0.00005539708,0.0005436767,0.00008486426,0.006477682],"genre_scores_gemma":[0.001030503,0.9874251,0.001774441,0.002115206,0.002069609,0.00007437484,0.001388219,0.00005801241,0.00406456],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01275384,"threshold_uncertainty_score":0.04266584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1870216824747654,"score_gpt":0.3729776136275121,"score_spread":0.1859559311527468,"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."}}