{"id":"W2594724108","doi":"10.1016/j.crad.2017.02.004","title":"Can contrast-enhanced MRI with gadoxetic acid predict liver failure and other complications after major hepatic resection?","year":2017,"lang":"en","type":"article","venue":"Clinical Radiology","topic":"Hepatocellular Carcinoma Treatment and Prognosis","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; Mount Sinai Hospital; University of Toronto","funders":"","keywords":"Gadoxetic acid; Medicine; Hepatectomy; Receiver operating characteristic; Magnetic resonance imaging; Logistic regression; Radiology; Liver failure; Internal medicine; Gastroenterology; Resection; Nuclear medicine; Surgery; Gadolinium DTPA","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":[0.001177516,0.0004976179,0.0007737303,0.001013085,0.0002607124,0.001088167,0.0004927532,0.001397676,0.001195685],"category_scores_gemma":[0.00811487,0.0002622758,0.000507682,0.001001235,0.0007806862,0.001466707,0.000322557,0.0009343979,0.0004445075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002517452,"about_ca_system_score_gemma":0.0005524044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001294083,"about_ca_topic_score_gemma":0.002061764,"domain_scores_codex":[0.999631,0.0001306023,0.00005712005,0.00003454124,0.00005988649,0.00008677119],"domain_scores_gemma":[0.9967533,0.001183565,0.0009374355,0.0001938267,0.0003550762,0.0005769348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005529874,0.00007965856,0.9890722,0.00003514447,0.00008430865,0.0005748227,0.00002768351,0.00008711756,0.0003593365,0.00003748098,0.0003098921,0.00877938],"study_design_scores_gemma":[0.00005180871,0.0005216695,0.9934453,0.0000555277,0.0002372554,0.002646577,0.0003479978,0.0008690704,0.0004979619,0.0003823658,0.0009169714,0.00002750847],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859172,0.007425634,0.0004274663,0.002193971,0.0002278833,0.00001928505,0.0001368788,0.00002119192,0.00363054],"genre_scores_gemma":[0.997005,0.001679509,0.0002646936,0.0002642444,0.0003530629,0.000006068044,0.0001633095,0.000004893764,0.000259151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001397676,"threshold_uncertainty_score":0.006227374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05993094615193167,"score_gpt":0.321801070656881,"score_spread":0.2618701245049493,"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."}}