{"id":"W4396957860","doi":"10.1093/jbi/wbae022","title":"3D CT Radiomic Analysis Improves Detection of Axillary Lymph Node Metastases Compared to Conventional Features in Patients With Locally Advanced Breast Cancer","year":2024,"lang":"en","type":"article","venue":"Journal of Breast Imaging","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; London Health Sciences Centre; Trillium Health Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Breast cancer; Radiology; Lymph node; Retrospective cohort study; Biopsy; Nomogram; Axillary lymph nodes; Cancer; Nuclear medicine; Oncology; 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":[0.0001265113,0.0001922266,0.0003779234,0.0003883437,0.00004310335,0.000034629,0.0001186419,0.00002020567,0.00001162775],"category_scores_gemma":[0.000009094867,0.0001492806,0.0002022865,0.0004845871,0.00006991073,0.0000340509,0.00005334123,0.00008912702,5.120796e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000163729,"about_ca_system_score_gemma":0.0001599361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003335443,"about_ca_topic_score_gemma":0.0001849306,"domain_scores_codex":[0.9988557,0.00005080485,0.0003781415,0.0002478303,0.0002712613,0.0001963229],"domain_scores_gemma":[0.999212,0.00002111634,0.0002312472,0.0001340896,0.0003227163,0.00007879996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004054482,0.0003494271,0.7397865,0.0001198878,0.004931927,0.00006042128,0.0001157747,0.01239953,0.1131849,0.000002239053,0.0001122754,0.1248827],"study_design_scores_gemma":[0.002192402,0.00005631812,0.9882049,0.0002716004,0.0007692018,0.0004896986,0.0001234117,0.000140903,0.007507753,0.000004873558,0.00007764338,0.000161291],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921956,0.004389843,0.002271275,0.0004238259,0.0001915885,0.0001105523,0.0003999785,0.000006385138,0.00001095378],"genre_scores_gemma":[0.9987842,0.00007907796,0.0008559726,0.00008759042,0.0001064739,0.00001109072,0.0000461853,0.00002106898,0.000008324248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2484184,"threshold_uncertainty_score":0.6087486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002576956256579997,"score_gpt":0.234184625792549,"score_spread":0.231607669535969,"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."}}