{"id":"W2085864051","doi":"10.1016/j.jmir.2010.04.001","title":"Computed Tomography: Physical Principles and Recent Technical Advances","year":2010,"lang":"en","type":"article","venue":"Journal of medical imaging and radiation sciences","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Computer science; Medical physics; Scanner; Correction for attenuation; Tomography; Detector; Iterative reconstruction; Focus (optics); Artificial intelligence; Radiology; Medicine; Physics; Positron emission tomography; Optics; Telecommunications","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":[0.000708728,0.00007791116,0.0001467679,0.0001356362,0.0001281354,0.00007634421,0.0001619844,0.00003101058,0.00001028087],"category_scores_gemma":[0.0002625084,0.0000546155,0.00002827102,0.000239239,0.0004914934,0.0004978048,0.00002646175,0.0004066004,3.687077e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006158526,"about_ca_system_score_gemma":0.00003822338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.801804e-7,"about_ca_topic_score_gemma":0.000001821789,"domain_scores_codex":[0.9989816,0.00001781697,0.0002275857,0.00009810208,0.0005315967,0.0001433187],"domain_scores_gemma":[0.9994375,0.0001920682,0.00008280461,0.00004161109,0.000048125,0.0001979566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004433058,0.00003604387,0.01381694,0.00002539618,0.00000969202,0.00001659785,0.0002929343,0.001043103,0.00495081,0.001449782,0.0002659802,0.9780883],"study_design_scores_gemma":[0.001334246,0.0001275962,0.08426359,0.0002653943,0.00004653803,0.001640523,0.00144426,0.6831864,0.003161413,0.006572485,0.2175214,0.0004361067],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9158969,0.02621816,0.04310993,0.01145488,0.002080965,0.00007803385,0.000001757096,0.0001268205,0.001032575],"genre_scores_gemma":[0.9888065,0.004206728,0.006386234,0.0001281177,0.0004657172,6.855101e-7,2.409568e-7,0.00000445973,0.000001328354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9776522,"threshold_uncertainty_score":0.2227155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00911857522593837,"score_gpt":0.2916025831942805,"score_spread":0.2824840079683421,"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."}}