{"id":"W3099026564","doi":"10.1002/mp.15007","title":"fastCAT: Fast cone beam CT (CBCT) simulation","year":2021,"lang":"en","type":"preprint","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Canada Research Chairs; Government of Canada","keywords":"Imaging phantom; Detector; Physics; Monte Carlo method; Optics; Cone beam computed tomography; Scintillator; Beam (structure); Detective quantum efficiency; Nuclear medicine; Materials science; Image quality; Computed tomography; Mathematics; Medicine; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007859587,0.0009122981,0.0005201019,0.000644926,0.0003985727,0.001306807,0.002080549,0.001290365,0.01027058],"category_scores_gemma":[0.002487646,0.0006805699,0.00090208,0.0007396755,0.0003631304,0.0007107554,0.0005811672,0.0007564069,0.00134463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001408883,"about_ca_system_score_gemma":0.002108428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01881326,"about_ca_topic_score_gemma":0.01647615,"domain_scores_codex":[0.9996963,0.00005689185,0.00002006969,0.00003423372,0.0001692149,0.00002345887],"domain_scores_gemma":[0.9987102,0.0005785293,0.00007120027,0.00008302511,0.0005025513,0.00005450884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001684142,0.00005380911,0.002004615,0.000244676,0.00007165874,0.0002336913,0.0001017817,0.9487595,0.005102599,0.004916797,0.01185378,0.02648869],"study_design_scores_gemma":[0.00002883755,0.00001861372,0.0002428707,0.00002048443,0.00001006727,0.00007228668,0.00001103188,0.9907085,0.002016883,0.0009871367,0.005867866,0.00001541002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0847683,0.001295157,0.8406577,0.0008522124,0.0002972995,0.001005232,0.01404794,0.02239418,0.03468201],"genre_scores_gemma":[0.6049278,0.001328847,0.3620394,0.0007105634,0.00006982138,0.001687206,0.01050656,0.005788829,0.01294099],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01881326,"threshold_uncertainty_score":0.03740752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501761484326358,"score_gpt":0.3078752242782833,"score_spread":0.2928576094350197,"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."}}