{"id":"W4294933008","doi":"10.1177/15330338221124695","title":"Comparison of Prospectively Generated Glioma Treatment Plans Clinically Delivered on Magnetic Resonance Imaging (MRI)-Linear Accelerator (MR-Linac) Versus Conventional Linac: Predicted and Measured Skin Dose","year":2022,"lang":"en","type":"article","venue":"Technology in Cancer Research & Treatment","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Linear particle accelerator; Magnetic resonance imaging; Nuclear medicine; Radiation treatment planning; Monte Carlo method; Radiation therapy; Dosimeter; Dosimetry; Imaging phantom; Medicine; Medical physics; Physics; Nuclear magnetic resonance; Radiology; Optics; Beam (structure); Mathematics","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":[0.001010607,0.0003529803,0.000292627,0.0002422074,0.0001002812,0.0003346912,0.0003853872,0.000296221,0.001274636],"category_scores_gemma":[0.003400991,0.0002760144,0.0004057579,0.0001867672,0.0002377633,0.0001949282,0.0002099972,0.0003100277,0.0002700094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00072102,"about_ca_system_score_gemma":0.0003176511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001626448,"about_ca_topic_score_gemma":0.001365724,"domain_scores_codex":[0.9995961,0.0001408067,0.00003195808,0.000108427,0.00009886665,0.00002388166],"domain_scores_gemma":[0.9979393,0.00124665,0.0003736001,0.0002379006,0.0001365059,0.00006618747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.01719365,0.001935794,0.3735347,0.0002148415,0.0007444538,0.0003051589,0.0005491175,0.4617923,0.05325066,0.0008257246,0.001562352,0.08809129],"study_design_scores_gemma":[0.001049442,0.02155369,0.4980288,0.00002719754,0.0004651943,0.001462293,0.0002463756,0.3843886,0.08934215,0.0005831951,0.002739159,0.0001139225],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942372,0.0001018922,0.004809924,0.00001669775,0.000006330616,0.00005454457,0.0002720233,0.0001172524,0.0003841414],"genre_scores_gemma":[0.9977803,0.00002191531,0.001544381,0.000007983035,0.000002672473,0.0000308423,0.0003732459,0.00002919867,0.0002096356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001626448,"threshold_uncertainty_score":0.005344689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08036365742159217,"score_gpt":0.435013220937771,"score_spread":0.3546495635161788,"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."}}