{"id":"W2523902566","doi":"10.1016/j.ijrobp.2016.06.298","title":"Serial 4-Dimensional (4D) Computed Tomography/4D Positron Emission Tomography Imaging to Predict and Monitor Response for Locally Advanced Non-Small Cell Lung Cancer Radiation Therapy","year":2016,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Medicine; Lung cancer; Radiation therapy; Radiation treatment planning; Positron emission tomography; Univariate analysis; Univariate; Nuclear medicine; Multivariate analysis; Radiology; Multivariate statistics; Internal medicine; Statistics","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":[0.0008403591,0.0006664371,0.0008390325,0.001193948,0.0002673209,0.0007939579,0.0006255386,0.000706027,0.000995873],"category_scores_gemma":[0.001647174,0.0003086398,0.0005837278,0.0005253947,0.0003611143,0.000567234,0.0002719953,0.0006844439,0.0002982799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005736557,"about_ca_system_score_gemma":0.0004391414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003404879,"about_ca_topic_score_gemma":0.004606464,"domain_scores_codex":[0.9997777,0.00005269533,0.00002863553,0.00004260022,0.00006044823,0.00003789234],"domain_scores_gemma":[0.9993524,0.0002026436,0.0001176362,0.0000568642,0.00016085,0.0001097109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007736602,0.001129993,0.8033862,0.0002196341,0.0004336669,0.00145685,0.0001555452,0.007691138,0.03277192,0.0001564059,0.002813181,0.142049],"study_design_scores_gemma":[0.0005464737,0.008016468,0.8523182,0.0001209887,0.001325473,0.004497738,0.0005593966,0.07821038,0.0461254,0.0009721259,0.007202399,0.0001048477],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859688,0.006136787,0.003045199,0.0006265065,0.0001589719,0.0001776801,0.0005152312,0.0001940345,0.003176631],"genre_scores_gemma":[0.9931414,0.001604127,0.003354247,0.0002020634,0.00009056237,0.00007510748,0.0006079748,0.00002320101,0.000901399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003404879,"threshold_uncertainty_score":0.006770134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007957377261884984,"score_gpt":0.3107699990131161,"score_spread":0.3028126217512311,"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."}}