{"id":"W2768252195","doi":"10.1097/md.0000000000008452","title":"Impact of iterative reconstruction vs. filtered back projection on image quality in 320-slice CT coronary angiography","year":2017,"lang":"en","type":"article","venue":"Medicine","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital","funders":"Bracco Diagnostics; Toshiba Medical Systems","keywords":"Medicine; Image quality; Radon transform; Iterative reconstruction; Interquartile range; Nuclear medicine; Image noise; Computed tomography angiography; Radiology; Angiography; Artificial intelligence; Image (mathematics); Surgery; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006259302,0.0003236484,0.0004960381,0.0005706784,0.0001534539,0.0009431622,0.0003577968,0.0004886709,0.0005804365],"category_scores_gemma":[0.02396476,0.0003072052,0.0005360203,0.0003631489,0.000501756,0.0004421821,0.0005524834,0.0002988882,0.0001653301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003335302,"about_ca_system_score_gemma":0.0002549639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005979824,"about_ca_topic_score_gemma":0.0007817578,"domain_scores_codex":[0.994329,0.003314248,0.0005097274,0.0003891297,0.001281566,0.0001762948],"domain_scores_gemma":[0.9844912,0.01067009,0.002038747,0.001026552,0.001495653,0.0002777087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03419667,0.0009106874,0.3692691,0.0007572289,0.001980628,0.001413451,0.001350259,0.03051604,0.2534837,0.0006114882,0.0005016681,0.305009],"study_design_scores_gemma":[0.0006260955,0.01780035,0.7648588,0.0001320132,0.001691361,0.007716909,0.0005003183,0.1017751,0.1029607,0.0006523138,0.001061134,0.0002248739],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880684,0.001095345,0.009978436,0.0000723206,0.000009708196,0.0000382574,0.00004042028,0.00006678351,0.0006303634],"genre_scores_gemma":[0.9902607,0.0002319295,0.009204574,0.00003663031,0.00001026704,0.00001642721,0.00006951185,0.00004909762,0.0001208963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006259302,"threshold_uncertainty_score":0.03310275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04537933316699608,"score_gpt":0.388932650167485,"score_spread":0.3435533170004889,"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."}}