{"id":"W4290723383","doi":"10.1186/s12880-022-00869-4","title":"Correction: Practical utility of liver segmentation methods in clinical surgeries and interventions","year":2022,"lang":"en","type":"erratum","venue":"BMC Medical Imaging","topic":"Hepatocellular Carcinoma Treatment and Prognosis","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Qatar National Library","keywords":"Computer science; Segmentation; Medical physics; Psychological intervention; Information retrieval; Data science; Radiology; General surgery; Artificial intelligence; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004488401,0.0002196821,0.000858073,0.0002546304,0.00007142428,0.00001995954,0.00007237207,0.0002859223,0.008065194],"category_scores_gemma":[0.007802692,0.0002005225,0.0004839541,0.0002771444,0.0004011094,0.0001102504,0.000218913,0.001615566,0.000004581266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008373947,"about_ca_system_score_gemma":0.00124501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002902013,"about_ca_topic_score_gemma":0.0002025792,"domain_scores_codex":[0.9955136,0.001886174,0.001219983,0.000484406,0.0006650451,0.0002307972],"domain_scores_gemma":[0.9961016,0.002896065,0.000350351,0.000272779,0.00009395534,0.0002852594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000118414,0.0004842176,0.6263772,0.001028079,0.00008193311,0.0003774067,0.0001030031,5.754591e-9,0.000001818875,0.000009781041,0.2560171,0.1154011],"study_design_scores_gemma":[0.003164894,0.0004333621,0.7009907,0.004430617,0.001895703,0.001056493,0.00137242,0.0836111,0.0001054768,0.00009061159,0.2023635,0.0004850704],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07312527,0.1702719,0.3555627,0.01980481,0.2574325,0.009438852,0.0002503718,0.0008257946,0.1132877],"genre_scores_gemma":[0.4346437,0.04532191,0.3290932,0.002768269,0.007439167,0.001633242,0.009021842,0.0004683934,0.1696103],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3615184,"threshold_uncertainty_score":0.9928415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2406689019480024,"score_gpt":0.4755266812904354,"score_spread":0.234857779342433,"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."}}