{"id":"W2060698963","doi":"10.1088/1742-6596/102/1/012017","title":"Fast Monte Carlo calculation of scatter corrections for CBCT images","year":2008,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Monte Carlo method; Variance reduction; Variance (accounting); Cone beam computed tomography; Algorithm; Reduction (mathematics); Computer science; Physics; Optics; Computed tomography; Mathematics; Statistics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004982616,0.0001128351,0.0002661478,0.00004519404,0.0001000632,0.00001554305,0.0001131716,0.0000222313,0.00003473595],"category_scores_gemma":[0.000005103239,0.00009889676,0.0001700367,0.00008355937,0.000140484,0.0005913868,0.00001146821,0.0001192412,2.947707e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001983191,"about_ca_system_score_gemma":0.0001074794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003270319,"about_ca_topic_score_gemma":0.000001364498,"domain_scores_codex":[0.9993574,0.00001915008,0.0003029043,0.00007999458,0.0001264716,0.0001140745],"domain_scores_gemma":[0.998763,0.00004158638,0.0004615587,0.0001147597,0.0005833507,0.00003576932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005376033,0.0007187008,0.150686,0.0001069923,0.0008469617,0.000005552552,0.01014922,0.008049821,0.3257451,0.04220385,0.006956561,0.4539936],"study_design_scores_gemma":[0.0005842776,0.0004232806,0.005695344,0.00008761834,0.00005363913,0.00001471972,0.0007217031,0.0003982161,0.9780717,0.01180052,0.001934255,0.0002146702],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1266209,0.00003501555,0.872533,0.0001100822,0.0001506941,0.0001253553,0.00004596856,0.00001187614,0.0003670856],"genre_scores_gemma":[0.9753844,0.00003100184,0.02374096,0.00001191076,0.0003830943,0.00000998834,0.000003655472,0.00001500197,0.0004200508],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8487921,"threshold_uncertainty_score":0.4032893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035822869669799,"score_gpt":0.2794653500136611,"score_spread":0.2591071213169631,"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."}}