{"id":"W2138482829","doi":"10.1148/rg.296095508","title":"Cirrhosis and Lesion Characterization at MR Imaging","year":2009,"lang":"en","type":"article","venue":"Radiographics","topic":"Hepatocellular Carcinoma Treatment and Prognosis","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Cirrhosis; Radiology; Lesion; Pathology; Internal medicine","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":[0.00006616877,0.0001150782,0.0001652597,0.0002243636,0.0001165202,0.00002219094,0.00002425004,0.00005736942,0.00002759017],"category_scores_gemma":[0.000008494408,0.0001014092,0.00009356733,0.0003207511,0.00003630748,0.00008171512,0.00001109412,0.0000694624,0.000006191055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002687675,"about_ca_system_score_gemma":0.000009718984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005084943,"about_ca_topic_score_gemma":8.826577e-7,"domain_scores_codex":[0.9993661,0.00002193295,0.0001256998,0.0001940227,0.0001340562,0.0001581751],"domain_scores_gemma":[0.9996392,0.00001534251,0.00004065084,0.0001488991,0.0000345813,0.0001213333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003719869,0.00005200792,0.9000312,0.00001630531,0.00001970432,0.0000548758,0.0001071426,8.360924e-9,0.05926615,0.0001316737,0.0001104883,0.04017323],"study_design_scores_gemma":[0.0008332969,0.0001826549,0.9806324,0.00005966564,0.0001899065,0.0001272722,0.000009473751,0.001848183,0.008248843,0.00007599454,0.007661364,0.0001309281],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994444,0.001580169,0.000190223,0.002869739,0.0000472071,0.0002346565,0.000005117997,0.00008538052,0.0005435468],"genre_scores_gemma":[0.9960362,0.002500812,0.0003433508,0.0006727815,0.00008216566,0.000006227234,0.0002009236,0.00001211855,0.0001453852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0806012,"threshold_uncertainty_score":0.4135348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03760976267802128,"score_gpt":0.244472536157198,"score_spread":0.2068627734791768,"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."}}