{"id":"W1949839429","doi":"10.1148/radiol.2015132766","title":"State of the Art: Iterative CT Reconstruction Techniques","year":2015,"lang":"en","type":"article","venue":"Radiology","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":701,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; Health Sciences Centre; University of British Columbia","funders":"","keywords":"Medicine; Iterative reconstruction; Image quality; Algorithm; Tomographic reconstruction; Noise (video); Projection (relational algebra); Radiation dose; Image processing; Tomography; Medical physics; Image (mathematics); Artificial intelligence; Nuclear medicine; Computer science; Radiology","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":[0.002638445,0.00114004,0.001050965,0.002317943,0.0004037047,0.002998203,0.002925174,0.002119535,0.009607732],"category_scores_gemma":[0.006625466,0.0007164447,0.00104191,0.003348421,0.001172823,0.002429373,0.001533167,0.003136255,0.01050277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000710585,"about_ca_system_score_gemma":0.001377076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001370111,"about_ca_topic_score_gemma":0.0007295471,"domain_scores_codex":[0.9974673,0.000636481,0.000204127,0.0003750215,0.001238225,0.00007891065],"domain_scores_gemma":[0.9966208,0.001765216,0.0002278443,0.0004059948,0.0008826197,0.00009754651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001115658,0.00005735695,0.0004647444,0.002094834,0.00007901532,0.0001280051,0.0001097988,0.005661225,0.004632751,0.01784379,0.01135891,0.957458],"study_design_scores_gemma":[0.00007005297,0.0003309651,0.001422796,0.003097104,0.0002626231,0.007037835,0.0001132951,0.104637,0.02227775,0.04256523,0.8179721,0.0002133145],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.001963413,0.2807498,0.692035,0.001921264,0.0008018222,0.0001466787,0.0002112165,0.001436449,0.02073442],"genre_scores_gemma":[0.04001088,0.3214242,0.6194347,0.001500805,0.002698553,0.0002743698,0.0009134517,0.0009780322,0.01276509],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.009607732,"threshold_uncertainty_score":0.03214109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01847956411274634,"score_gpt":0.2829636941664656,"score_spread":0.2644841300537193,"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."}}