{"id":"W4280507273","doi":"10.1097/rlu.0000000000004253","title":"Combined 18F-FDG PET/CT Radiomics and Sarcopenia Score in Predicting Relapse-Free Survival and Overall Survival in Patients With Esophagogastric Cancer","year":2022,"lang":"en","type":"article","venue":"Clinical Nuclear Medicine","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Toronto General Hospital; University Health Network; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Sarcopenia; Radiomics; Cancer; Stage (stratigraphy); Internal medicine; Esophageal cancer; Adenocarcinoma; Positron emission tomography; Radiology; Oncology","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":[0.00110193,0.0007119533,0.000568276,0.0007144613,0.0002136419,0.0005862005,0.0004089376,0.0005813531,0.0008660529],"category_scores_gemma":[0.002515405,0.0002183016,0.0007481531,0.0004518005,0.0002139932,0.0003839147,0.0004402091,0.0005409381,0.0002258675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001841049,"about_ca_system_score_gemma":0.0002420615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001035312,"about_ca_topic_score_gemma":0.002448358,"domain_scores_codex":[0.9996336,0.000152699,0.00003786806,0.00007314974,0.00006031312,0.00004239865],"domain_scores_gemma":[0.999236,0.0002244613,0.0002045211,0.00006286014,0.0001038176,0.0001682884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002516912,0.00002631901,0.9969132,0.00000735902,0.00008419319,0.00003538273,0.00001226455,0.0002848189,0.0001659803,0.000003100369,0.00004744841,0.00216823],"study_design_scores_gemma":[0.00003143853,0.0004075854,0.9908857,0.00001373949,0.0002212261,0.0002969773,0.00009767726,0.007656232,0.000175061,0.00004985789,0.0001563204,0.000008155261],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991635,0.0003104542,0.0002668293,0.00004259695,0.000008279938,0.000005864763,0.00008174633,0.000006567358,0.0001140484],"genre_scores_gemma":[0.9995912,0.00004760192,0.0001485399,0.00001122205,0.00001123436,0.000005131024,0.000123506,0.000001368379,0.00006033732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00110193,"threshold_uncertainty_score":0.005827606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02079249347028335,"score_gpt":0.3057204929899885,"score_spread":0.2849279995197052,"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."}}