{"id":"W4307292469","doi":"10.1016/j.ijrobp.2022.07.478","title":"Daily Assessment of On-Treatment Tumor Regression by Cone Beam CT as a Prognostic Dynamic Biomarker in Nasopharyngeal Cancer","year":2022,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto","funders":"","keywords":"Medicine; Radiation therapy; Chemoradiotherapy; Stage (stratigraphy); Nuclear medicine; Cone beam computed tomography; Radiation treatment planning; Head and neck cancer; Clinical endpoint; Surrogate endpoint; Area under the curve; Internal medicine; Radiology; Clinical trial; Computed tomography","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":[0.0005355204,0.0002763536,0.0005213574,0.0005642556,0.000217509,0.0007584883,0.0003769626,0.000467426,0.0005259226],"category_scores_gemma":[0.001584718,0.0001571672,0.0002412988,0.0005224668,0.0002206743,0.0004038132,0.00027373,0.0004299866,0.000162625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004933442,"about_ca_system_score_gemma":0.0003258537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004038028,"about_ca_topic_score_gemma":0.004907708,"domain_scores_codex":[0.9996231,0.00007612014,0.00002551116,0.00008270347,0.0001466937,0.00004593047],"domain_scores_gemma":[0.9993112,0.0001501768,0.0002055783,0.00007240618,0.0001785116,0.00008209689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00274883,0.0003976471,0.8574508,0.0001071681,0.0001503537,0.0002710378,0.0003086451,0.001948488,0.02891811,0.00007971013,0.000806685,0.1068125],"study_design_scores_gemma":[0.00001275684,0.001111087,0.9845575,0.00001673644,0.000114851,0.0004028439,0.0002006242,0.006107742,0.005821583,0.00007642925,0.001553259,0.00002461518],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961022,0.001228102,0.0007575965,0.00005927148,0.00003056865,0.00003789498,0.0003165285,0.0000522522,0.001415604],"genre_scores_gemma":[0.998582,0.0002622211,0.000444188,0.00001921766,0.00001345228,0.00001673812,0.0002405647,0.00001238358,0.0004092955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004038028,"threshold_uncertainty_score":0.008029044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01320824263235258,"score_gpt":0.3676013804026054,"score_spread":0.3543931377702528,"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."}}