{"id":"W2006392344","doi":"10.1118/1.3017470","title":"The influence of bowtie filtration on cone‐beam CT image quality","year":2008,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":176,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto; Ontario Institute for Cancer Research","funders":"","keywords":"Imaging phantom; Image quality; Cone beam computed tomography; Optics; Flat panel detector; Detector; Nuclear medicine; Filter (signal processing); Dosimetry; Medical imaging; Physics; Medicine; Computer science; Image (mathematics); Radiology; Computed tomography; Artificial intelligence; Computer vision","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":[0.0001817954,0.00009905449,0.0001560772,0.000006759333,0.0001472919,0.000006452014,0.0002081536,0.00001921709,0.00007004206],"category_scores_gemma":[0.0000516279,0.00006825549,0.00007084854,0.00009261246,0.0004266297,0.0001065081,0.00001991097,0.0002161119,0.000006308749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001663318,"about_ca_system_score_gemma":0.00008161383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007653578,"about_ca_topic_score_gemma":4.856649e-7,"domain_scores_codex":[0.9990176,0.00004899972,0.0002373181,0.0001310385,0.0004173825,0.0001476628],"domain_scores_gemma":[0.9991644,0.0002933394,0.0001354306,0.0002813195,0.00006129359,0.00006423188],"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":[0.0003088065,0.002666124,0.1221448,0.0001034478,0.0004376433,0.0000301041,0.002077235,0.001058402,0.0911441,0.3373298,0.02207221,0.4206274],"study_design_scores_gemma":[0.001392215,0.000373389,0.04789807,0.0001311087,0.00001814263,0.000003720259,0.00006519918,0.0003801834,0.825026,0.1080918,0.0160646,0.0005556506],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8535004,0.00002347576,0.1429414,0.0002672452,0.00004825112,0.000157939,0.00001709826,0.00005567533,0.0029885],"genre_scores_gemma":[0.9989019,0.00003442369,0.0005027193,0.000188108,0.0002478945,0.00002158319,0.00001071341,0.00001123322,0.00008144883],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7338818,"threshold_uncertainty_score":0.2783378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01496669444505642,"score_gpt":0.3159500816376967,"score_spread":0.3009833871926402,"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."}}