{"id":"W4413842489","doi":"10.2340/1651-226x.2025.43977","title":"External validation of deep learning-derived 18F-FDG PET/CT delta biomarkers for loco-regional control in head and neck cancer","year":2025,"lang":"en","type":"article","venue":"Acta Oncologica","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"Manchester Biomedical Research Centre; Hartmann Fonden; National Institute for Health and Care Research; Cancer Research UK","keywords":"Medicine; Head and neck cancer; Head and neck; Cancer; PET-CT; Nuclear medicine; Computed tomography; Positron emission tomography; Radiology; Radiation therapy; Surgery; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005694324,0.0008557983,0.0004341941,0.0005971697,0.0002531274,0.0007112483,0.001095348,0.0009763253,0.0008595089],"category_scores_gemma":[0.008072271,0.0002306507,0.0005636404,0.0003603016,0.0008414424,0.0003520029,0.001121507,0.0007306193,0.0005955662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009815805,"about_ca_system_score_gemma":0.0008414264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00423828,"about_ca_topic_score_gemma":0.003782008,"domain_scores_codex":[0.9986569,0.0005367003,0.00008571339,0.0003690763,0.0002557717,0.00009588474],"domain_scores_gemma":[0.9964409,0.001500331,0.0003850617,0.0005651965,0.0009317693,0.0001766177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.004612386,0.001725632,0.3081482,0.0005253879,0.0009563723,0.0003764629,0.0004642934,0.3798461,0.04346719,0.0005866785,0.005029993,0.2542613],"study_design_scores_gemma":[0.000266595,0.001724377,0.08467308,0.00009793362,0.0001935356,0.0003069853,0.0001201894,0.8780339,0.03203072,0.0005446647,0.001964885,0.00004317217],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747427,0.0004165667,0.02147377,0.00013186,0.00005962983,0.0002679758,0.0009786532,0.0007071241,0.001221784],"genre_scores_gemma":[0.9906678,0.00005101368,0.006292132,0.00005979041,0.000009485701,0.0001086865,0.002323089,0.00003605384,0.0004521016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005694324,"threshold_uncertainty_score":0.03011483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0314947959446674,"score_gpt":0.3486532194087128,"score_spread":0.3171584234640454,"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."}}