{"id":"W3195339042","doi":"10.21203/rs.3.rs-807483/v1","title":"Clinically Delivered Treatment for Glioma Patients on a Hybrid Magnetic Resonance Imaging (MRI)-Linear Accelerator (MR-Linac) and a Cone Beam CT (CBCT)-Guided Linac: Dosimetric Comparisons with In Vivo Skin Dose Correlation","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"Accuray; Elekta","keywords":"Linear particle accelerator; Nuclear medicine; Magnetic resonance imaging; Medicine; Cone beam ct; Beam (structure); Medical physics; Radiology; Physics; Optics; 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":[0.0001744239,0.0001827466,0.0002997543,0.0002167324,0.0001914508,0.0001500542,0.0001728619,0.0001899643,0.001072324],"category_scores_gemma":[0.0007615559,0.000128044,0.0002433054,0.0001456859,0.0001706679,0.00009055206,0.0001685847,0.0001562114,0.0001976852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005181627,"about_ca_system_score_gemma":0.0002951093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001524859,"about_ca_topic_score_gemma":0.003160847,"domain_scores_codex":[0.9998222,0.00005939577,0.00001056306,0.00003310532,0.0000424221,0.00003226522],"domain_scores_gemma":[0.9998009,0.00006438555,0.00005808961,0.00001936783,0.00001820305,0.00003915836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01762361,0.001686079,0.691476,0.0001867647,0.0003290194,0.001702468,0.0008584409,0.01511805,0.1839411,0.0003021683,0.001138655,0.08563762],"study_design_scores_gemma":[0.0005544134,0.02297513,0.9291291,0.00001083236,0.0002093136,0.003964057,0.0002039524,0.007528142,0.03314467,0.0001876681,0.002060913,0.00003181029],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991214,0.00009787019,0.0004452915,0.00001044693,0.00000168538,0.00002434788,0.00005581987,0.00001023297,0.0002329224],"genre_scores_gemma":[0.9992533,0.00002793065,0.0004438686,0.000008105185,0.000001996926,0.00002049334,0.00009708138,0.000003609808,0.000143536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001524859,"threshold_uncertainty_score":0.003759503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06654707690295403,"score_gpt":0.3861043314411134,"score_spread":0.3195572545381594,"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."}}