{"id":"W2615357223","doi":"10.1016/j.ejca.2017.07.054","title":"Cost-effectiveness analysis of PET-CT-guided management for locally advanced head and neck cancer","year":2017,"lang":"en","type":"article","venue":"European Journal of Cancer","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Health Technology Assessment Programme; National Institute for Health and Care Research","keywords":"Head and neck cancer; Medicine; Head and neck; Medical physics; PET-CT; Cost-effectiveness analysis; Radiology; Nuclear medicine; Cost effectiveness; Computed tomography; Radiation therapy; Surgery; Risk analysis (engineering)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007132691,0.0001586221,0.0007937195,0.0001953818,0.0001710133,0.00002718138,0.0001772199,0.000005758322,0.00005281041],"category_scores_gemma":[0.00008974917,0.0001207448,0.0002499783,0.0001364038,0.0001275468,0.0001219377,0.00007563655,0.0001213538,7.362967e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001283323,"about_ca_system_score_gemma":0.000098016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000685281,"about_ca_topic_score_gemma":0.0001366445,"domain_scores_codex":[0.9987539,0.00009067846,0.0004724553,0.0001936883,0.0002785291,0.000210721],"domain_scores_gemma":[0.9983571,0.00005834005,0.0006341802,0.0002891994,0.0005113255,0.0001498446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003739291,0.0001990722,0.2284472,0.001185331,0.01214957,0.001248047,0.0005445022,0.002098753,0.003181781,0.0001287728,0.00379014,0.7432875],"study_design_scores_gemma":[0.00805872,0.0006663682,0.9179235,0.001795159,0.003392889,0.00003916628,0.0001124542,0.0002061913,0.001832118,0.000009657887,0.06581454,0.000149222],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800597,0.009590403,0.001102582,0.001427061,0.0005095896,0.0005784561,0.00004469379,0.000007592902,0.006679884],"genre_scores_gemma":[0.9890184,0.008612007,0.001046651,0.000268535,0.0002037721,0.00003291876,0.000001357054,0.00003007674,0.0007862591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7431383,"threshold_uncertainty_score":0.4923829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06751163539046229,"score_gpt":0.4024318930183756,"score_spread":0.3349202576279133,"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."}}