{"id":"W1969878828","doi":"10.1118/1.4861818","title":"A Monte Carlo investigation of low‐Z target image quality generated in a linear accelerator using Varianˈs VirtuaLinac<sup>a)</sup>","year":2014,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Truebeam; Monte Carlo method; Linear particle accelerator; Imaging phantom; Physics; Photon; Optics; Detector; Dosimetry; Nuclear medicine; Computational physics; Beam (structure); Mathematics; Medicine; Statistics","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":[0.0005703153,0.0002214191,0.0004626123,0.00004973298,0.00005741672,0.00001783575,0.0002443343,0.0001134255,0.0001441532],"category_scores_gemma":[0.00008161087,0.0002110343,0.00009858577,0.0003826887,0.0002194046,0.0002613745,0.0000626609,0.0003761699,0.000002523356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006434521,"about_ca_system_score_gemma":0.0001937604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006408169,"about_ca_topic_score_gemma":0.00000209232,"domain_scores_codex":[0.9981043,0.0002816379,0.0005616673,0.0003194255,0.0004492729,0.0002837205],"domain_scores_gemma":[0.9989848,0.0001270113,0.0002341335,0.0003387247,0.0001366178,0.0001787209],"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":[0.000397315,0.002913558,0.3399133,0.0007673723,0.0006735685,0.00002800586,0.01335972,0.0637383,0.4600588,0.04131484,0.001972893,0.07486238],"study_design_scores_gemma":[0.001656121,0.0001054988,0.0009275543,0.0002042926,0.00002010993,5.247359e-7,0.00007651905,0.8010573,0.1759944,0.0190534,0.0004217997,0.0004824644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5200252,0.0000134787,0.4795894,0.00006039125,0.00003713635,0.000144305,0.00002403261,0.00004258452,0.00006346127],"genre_scores_gemma":[0.9530251,0.000002909289,0.04580286,0.0002581785,0.0007874696,0.00002603762,0.0000383484,0.00004139587,0.00001769067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7373191,"threshold_uncertainty_score":0.8605728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02197782007171868,"score_gpt":0.3101565376360688,"score_spread":0.2881787175643502,"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."}}