{"id":"W2060193743","doi":"10.1118/1.2358324","title":"Characterization of scattered radiation in kV CBCT images using Monte Carlo simulations","year":2006,"lang":"en","type":"article","venue":"Medical Physics","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":187,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Ontario Institute for Cancer Research; University of Toronto; University Health Network; McGill University","funders":"","keywords":"Monte Carlo method; Characterization (materials science); Radiation transport; Medical physics; Dosimetry; Medical imaging; Radiation; Radiation dose; Physics; Optics; Statistical physics; Nuclear medicine; Computer science; Medicine; Mathematics; Artificial intelligence; 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":[0.00009102684,0.00007436499,0.0001845865,0.00008323507,0.00002789283,0.000008848215,0.00004065985,0.00005160226,0.0000571714],"category_scores_gemma":[0.00008761259,0.0000726295,0.00004229374,0.0002941579,0.00005235787,0.0001981736,0.0000110078,0.0001073403,0.00000427858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006124726,"about_ca_system_score_gemma":0.0001004808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002431832,"about_ca_topic_score_gemma":0.000006205245,"domain_scores_codex":[0.9990942,0.00002801684,0.0003000303,0.0001199085,0.0003389488,0.0001188763],"domain_scores_gemma":[0.9996244,0.00004016066,0.0001099391,0.0001209261,0.00005056537,0.00005406122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004047625,0.0005339456,0.4938067,0.0001240422,0.00003250449,0.00001702423,0.0004152899,0.004711397,0.4257331,0.0001329775,0.0002424176,0.07421009],"study_design_scores_gemma":[0.001776363,0.00003048544,0.6448912,0.0001910762,0.00005464698,0.000004504754,0.00001169754,0.2336131,0.1187036,0.0003460561,0.0002507388,0.0001264535],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841791,0.0000405465,0.01444323,0.0008744774,0.00008119927,0.0001543909,0.00001417542,0.00002048547,0.0001923576],"genre_scores_gemma":[0.9989356,0.00001188939,0.00009282513,0.0002674508,0.0004640976,0.000002415073,0.0001556794,0.00001289627,0.00005711391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3070295,"threshold_uncertainty_score":0.2961745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01518938953311599,"score_gpt":0.285015936575275,"score_spread":0.269826547042159,"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."}}