{"id":"W2029312015","doi":"10.1118/1.4814606","title":"SU‐E‐T‐171: Pre‐Treatment Radiotherapy Dose Verification Using Monte Carlo Doselet Modulation in a Spherical Phantom","year":2013,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; University of Victoria","funders":"","keywords":"Imaging phantom; Monte Carlo method; Voxel; Physics; Symmetry (geometry); RADIUS; Dosimetry; Radiation treatment planning; Circular symmetry; Nuclear medicine; Optics; Computational physics; Geometry; Radiation therapy; Mathematics; Computer science; Medicine; Radiology","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":[0.001337879,0.0004742461,0.0002895143,0.0003204482,0.0001826153,0.0005799317,0.0009312473,0.0004300528,0.002443361],"category_scores_gemma":[0.003140045,0.0003875683,0.0003642059,0.0002757535,0.0003230999,0.0003980538,0.0005270259,0.0003630498,0.0007536788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005459936,"about_ca_system_score_gemma":0.000691359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008108211,"about_ca_topic_score_gemma":0.0006868499,"domain_scores_codex":[0.9994738,0.000144548,0.0000301383,0.00006179108,0.0002571225,0.00003267927],"domain_scores_gemma":[0.99919,0.0002816221,0.0001619399,0.0001717213,0.0001550949,0.00003951727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002158462,0.0002464174,0.005543394,0.0004914767,0.0001440315,0.0003985375,0.0003576331,0.2670744,0.5384662,0.0080154,0.003550976,0.1735531],"study_design_scores_gemma":[0.0001119576,0.0007711846,0.004524401,0.00002319601,0.00005462771,0.0007558272,0.00003171206,0.5077132,0.4754242,0.0008511445,0.009665281,0.00007330897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1040108,0.0002676309,0.8834965,0.0001211306,0.0000304525,0.0002414379,0.0002123468,0.005862259,0.005757479],"genre_scores_gemma":[0.6132381,0.0001130741,0.3811896,0.0001048809,0.0000112425,0.0002272164,0.0004593085,0.001390765,0.003265751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002443361,"threshold_uncertainty_score":0.008173883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01586199610348075,"score_gpt":0.3014724909289699,"score_spread":0.2856104948254892,"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."}}