{"id":"W3164972140","doi":"10.1016/j.adro.2021.100727","title":"Magnetic Resonance Imaging for Breast Tumor Bed Delineation: Computed Tomography Comparison and Sequence Variation","year":2021,"lang":"en","type":"article","venue":"Advances in Radiation Oncology","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre; University Health Network","funders":"Canadian Cancer Society","keywords":"Medicine; Magnetic resonance imaging; Breast cancer; Nuclear medicine; Supine position; Radiation therapy; Computed tomography; Radiology; Cancer; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002322915,0.0001252549,0.0003453608,0.0001697382,0.00007058238,0.00001742742,0.00005701866,0.00006346506,0.00006627281],"category_scores_gemma":[0.0001387338,0.0001428853,0.00004033845,0.0005268867,0.0000898227,0.0002761357,0.00002312692,0.0001323306,0.000002322588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003196932,"about_ca_system_score_gemma":0.0002456374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000244284,"about_ca_topic_score_gemma":0.0002435965,"domain_scores_codex":[0.9986983,0.0001057385,0.0004450854,0.0003923331,0.0001418196,0.0002167342],"domain_scores_gemma":[0.998689,0.0005933968,0.0001833233,0.000172806,0.0002872278,0.00007423969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001605502,0.0001439568,0.4384745,0.00008362508,0.00000525227,0.0000290129,0.0002890573,0.0007646693,0.0006006333,0.0009376549,0.0005027728,0.5580083],"study_design_scores_gemma":[0.004914582,0.0003786438,0.5786695,0.0001587495,0.00007213621,0.0003601028,0.0001849723,0.1459266,0.0008667467,0.001004424,0.2672569,0.0002066325],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2399982,0.4813434,0.1738318,0.09114659,0.004875999,0.005148401,0.0005694494,0.0004717451,0.002614336],"genre_scores_gemma":[0.9179526,0.005738334,0.07246932,0.002791559,0.0003962157,0.0003734783,0.0002206077,0.0000244376,0.00003345521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6779544,"threshold_uncertainty_score":0.5826694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0170864090076809,"score_gpt":0.3562030212850021,"score_spread":0.3391166122773213,"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."}}