{"id":"W3164329335","doi":"10.1007/s00261-021-03098-5","title":"Correction to: Artificial intelligence in assessment of hepatocellular carcinoma treatment response","year":2021,"lang":"en","type":"article","venue":"Abdominal Radiology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thunder Bay Regional Health Sciences Centre","funders":"","keywords":"Hepatology; Hepatocellular carcinoma; Medicine; Internal medicine; Carcinoma; Medical physics; Gastroenterology","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":[0.000609869,0.0001148944,0.00042228,0.0001831834,0.00002956753,0.000005087737,0.00005539828,0.00006665254,0.000143236],"category_scores_gemma":[0.001041646,0.0001023378,0.00008966312,0.0002745688,0.0000887959,0.00001599475,0.00002761976,0.0002397769,0.00001001083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002905689,"about_ca_system_score_gemma":0.0004216464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002975722,"about_ca_topic_score_gemma":0.00003124779,"domain_scores_codex":[0.9986377,0.0003408765,0.0003878428,0.000286873,0.0001231523,0.000223586],"domain_scores_gemma":[0.9989808,0.0005250138,0.00006737085,0.0002262669,0.00007134965,0.0001292675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003510679,0.0006551482,0.4108874,0.00003807169,0.00007372818,0.003179746,0.001127225,0.001437692,0.3581107,0.001395568,0.0004568382,0.2191272],"study_design_scores_gemma":[0.0009270883,0.003212308,0.4857486,0.0001488587,0.0001080397,0.00257011,0.0009517295,0.4356068,0.06791734,0.000403247,0.002210671,0.0001952812],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9686279,0.0001717901,0.02659233,0.002899315,0.0008158244,0.0001909792,0.00000116051,0.00001161861,0.0006890712],"genre_scores_gemma":[0.9909817,0.00004444093,0.008082731,0.0003203506,0.0001207852,0.00002411652,0.00001290331,0.00001203536,0.0004009345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4341691,"threshold_uncertainty_score":0.4173216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02369701152282805,"score_gpt":0.3438585716478595,"score_spread":0.3201615601250315,"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."}}