{"id":"W2519502486","doi":"10.1097/01.jto.0000284174.03442.4f","title":"P3-199: CT, FDG PET and pathology: validating imaging to improve radiation targeting in non–small cell lung cancer (NSCLC)","year":2007,"lang":"en","type":"article","venue":"Journal of Thoracic Oncology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto General Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Lung cancer; Radiation therapy; PET-CT; Positron emission tomography; Radiology; Nuclear medicine; Pathology","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":[0.001803525,0.0004730746,0.0004401822,0.0008624303,0.0003132426,0.001201547,0.000635454,0.001296557,0.002696814],"category_scores_gemma":[0.00503128,0.0003042899,0.0003954091,0.0005129779,0.0005516097,0.0007332286,0.0004486738,0.000687587,0.001200385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005516417,"about_ca_system_score_gemma":0.0006282119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002292682,"about_ca_topic_score_gemma":0.003011869,"domain_scores_codex":[0.9996076,0.0001274554,0.00004127661,0.00005377431,0.0001323388,0.00003759676],"domain_scores_gemma":[0.998673,0.0006977397,0.0001469945,0.0001167271,0.0002781965,0.00008730406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01096722,0.0009976695,0.4140376,0.0005633998,0.00040722,0.004041281,0.0001982591,0.003474682,0.2847704,0.0008673012,0.007003136,0.2726718],"study_design_scores_gemma":[0.0007333726,0.005827643,0.5876936,0.000158912,0.000889601,0.02865784,0.0002835975,0.04156723,0.317,0.001961858,0.01512719,0.00009911026],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811614,0.003687656,0.005439157,0.0008144661,0.0001191617,0.0001395759,0.0008307704,0.0002915219,0.007516312],"genre_scores_gemma":[0.9879089,0.0005288043,0.008902158,0.0002055141,0.00004942754,0.00006050575,0.0008207629,0.00008513958,0.001438813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002696814,"threshold_uncertainty_score":0.009538114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007196511881390643,"score_gpt":0.37959060255778,"score_spread":0.3723940906763894,"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."}}