{"id":"W3109359120","doi":"10.1038/s41598-020-77740-5","title":"Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous 18F-FDG-PET and MRI","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Bone and Joint Diseases","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Cancer Institute; National Institutes of Health; School of Medicine, New York University; National Institute of Biomedical Imaging and Bioengineering; York University; Center for Advanced Imaging Innovation and Research","keywords":"Medicine; Lymph; Lymph node; Head and neck squamous-cell carcinoma; Positron emission tomography; Magnetic resonance imaging; Nuclear medicine; Diffusion MRI; Standardized uptake value; Neck dissection; Radiology; Metastasis; Head and neck cancer; Pathology; Carcinoma; Cancer; Radiation therapy; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005384722,0.000255237,0.0002111082,0.0005435844,0.0001307072,0.0002377044,0.0001311637,0.0002365207,0.0004569978],"category_scores_gemma":[0.0009409995,0.0001935388,0.0001383935,0.0001206934,0.0001658386,0.0003300092,0.0001818074,0.0001173563,0.0001442513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001302306,"about_ca_system_score_gemma":0.0001289324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007073801,"about_ca_topic_score_gemma":0.00187952,"domain_scores_codex":[0.9998698,0.00004238231,0.00001020637,0.000023483,0.00003393907,0.00002010622],"domain_scores_gemma":[0.9998316,0.00006354103,0.00002512789,0.00001320658,0.00003971513,0.00002682631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001072548,0.00008529732,0.8304187,0.0001265426,0.00006287186,0.002458078,0.000172339,0.0005301082,0.1259766,0.00005211803,0.0001013399,0.03894354],"study_design_scores_gemma":[0.00007021313,0.001663792,0.9349748,0.00004478542,0.0002015268,0.01909934,0.0007127518,0.006017214,0.03522638,0.0001545229,0.00180232,0.00003231531],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973761,0.001178903,0.001008892,0.00001296179,0.000005131376,0.00001328743,0.00002499251,0.000008013486,0.0003717194],"genre_scores_gemma":[0.9981913,0.0002907852,0.001330864,0.000008137412,0.000006973359,0.000009141532,0.00003766938,0.000001419337,0.0001236869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007073801,"threshold_uncertainty_score":0.002847731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03108653202372144,"score_gpt":0.3032588907192951,"score_spread":0.2721723586955737,"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."}}