{"id":"W4402467988","doi":"10.1101/2024.09.11.24313485","title":"Computed tomography radiomics-based cross-sectional detection of mandibular osteoradionecrosis in head and neck cancer survivors","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Oral health in cancer treatment","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre","funders":"National Institute of Dental and Craniofacial Research; University of Texas MD Anderson Cancer Center; National Institutes of Health; National Cancer Institute; ZonMw","keywords":"Osteoradionecrosis; Head and neck cancer; Radiomics; Medicine; Computed tomography; Radiology; Head and neck; Radiation therapy; 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":[0.0003637104,0.0002297672,0.0002100461,0.001274315,0.0001034692,0.0003095891,0.0001710051,0.0003084789,0.0006199828],"category_scores_gemma":[0.001432101,0.0001106148,0.0002592373,0.0003675861,0.0001459385,0.0001722265,0.0002652756,0.0001309902,0.0001513747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001717138,"about_ca_system_score_gemma":0.0001123788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001818648,"about_ca_topic_score_gemma":0.003042025,"domain_scores_codex":[0.9998709,0.00002396716,0.00001631737,0.00002942896,0.00004143683,0.0000178756],"domain_scores_gemma":[0.9996432,0.00008969095,0.0001399004,0.00002819397,0.00007508546,0.00002392282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002872893,0.00003018397,0.9746947,0.00003037149,0.00006079227,0.0001510516,0.00007223964,0.0009121202,0.0093181,0.00002008639,0.0001054708,0.01431747],"study_design_scores_gemma":[0.000003179199,0.00007704087,0.9932621,0.00000596746,0.00004739403,0.0005632761,0.0001092226,0.004171594,0.001570448,0.00002356948,0.0001623618,0.00000401382],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986925,0.0001924211,0.0007039677,0.00001176592,0.000001824755,0.000008811633,0.0001954755,0.00001303928,0.000180198],"genre_scores_gemma":[0.9991363,0.00005388737,0.0004592841,0.000005366799,0.000003207542,0.000005796749,0.0002707332,0.000001921323,0.00006364847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001818648,"threshold_uncertainty_score":0.003616154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03432524567556809,"score_gpt":0.3497227832769735,"score_spread":0.3153975376014054,"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."}}