{"id":"W4210520314","doi":"10.1016/j.ijrobp.2022.01.050","title":"Comprehensive Quantitative Evaluation of Variability in Magnetic Resonance-Guided Delineation of Oropharyngeal Gross Tumor Volumes and High-Risk Clinical Target Volumes: An R-IDEAL Stage 0 Prospective Study","year":2022,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre","funders":"National Institute of Dental and Craniofacial Research; National Institute of Biomedical Imaging and Bioengineering; National Cancer Institute","keywords":"Medicine; Magnetic resonance imaging; Head and neck cancer; Nuclear medicine; Stage (stratigraphy); Radiology; Institutional review board; Radiation therapy; Gold standard (test); Medical physics; Surgery","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":[0.003736082,0.0004245894,0.0003872894,0.0004650002,0.0002902472,0.0006149726,0.0005000872,0.0004679215,0.00067705],"category_scores_gemma":[0.004995317,0.0002896412,0.000366817,0.0002916018,0.0007535438,0.0006318201,0.000609095,0.0003590901,0.0002100823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003087528,"about_ca_system_score_gemma":0.0003538231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001078748,"about_ca_topic_score_gemma":0.0009741942,"domain_scores_codex":[0.9990012,0.0004056374,0.00005534619,0.0002960007,0.0001671111,0.00007468712],"domain_scores_gemma":[0.9953549,0.002034048,0.0008424975,0.001102595,0.0003944366,0.0002716555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02134651,0.001659621,0.9221796,0.0000702674,0.0005405553,0.0002192488,0.0008697773,0.00455464,0.02564919,0.0001963558,0.0002524983,0.02246161],"study_design_scores_gemma":[0.0002323696,0.006813549,0.9830933,0.000005320905,0.0001601862,0.0004579001,0.0002298714,0.005309687,0.003184362,0.0001320391,0.0003398876,0.00004166085],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993038,0.00005359743,0.000468502,0.000002174004,0.000001327829,0.00001132687,0.00007094081,0.000005982866,0.00008245683],"genre_scores_gemma":[0.9994368,0.0000140466,0.000342837,0.000004339144,0.000003303903,0.000009076455,0.0001237372,0.000007735818,0.00005819658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003736082,"threshold_uncertainty_score":0.01975852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06657668158867787,"score_gpt":0.4227288227355428,"score_spread":0.3561521411468649,"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."}}