{"id":"W2050476332","doi":"10.1016/j.jcct.2015.04.004","title":"Iterative reconstruction in cardiac CT","year":2015,"lang":"en","type":"review","venue":"Journal of cardiovascular computed tomography","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"","keywords":"Medicine; Iterative reconstruction; Image quality; Radiation dose; Radiology; Cardiac imaging; Image noise; Medical physics; Computed tomography; Noise (video); Nuclear medicine; Artificial intelligence; Image (mathematics); 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":[0.002344987,0.001251955,0.002041775,0.002347955,0.000223008,0.002071956,0.001949361,0.002204485,0.004087648],"category_scores_gemma":[0.006994906,0.001011768,0.001274841,0.002703723,0.001530191,0.001613169,0.001312073,0.003526663,0.00172601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006875959,"about_ca_system_score_gemma":0.001839148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002384728,"about_ca_topic_score_gemma":0.002180835,"domain_scores_codex":[0.9991366,0.0003036642,0.0001375577,0.000119137,0.0002608993,0.00004222532],"domain_scores_gemma":[0.9965238,0.002687663,0.0002363372,0.0001181536,0.0003636504,0.00007044563],"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":[0.0001159504,0.00006677098,0.0004311648,0.01773212,0.0003035913,0.0002557604,0.00009003442,0.005064373,0.001552054,0.004573673,0.01471798,0.9550967],"study_design_scores_gemma":[0.0002577589,0.0004953485,0.004665788,0.02349755,0.001832904,0.01620726,0.0001914495,0.02387386,0.007118778,0.01980006,0.9016569,0.0004025421],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002748449,0.9913412,0.00679248,0.0002875059,0.0002209846,0.00001057155,0.0000209106,0.00004209239,0.001009454],"genre_scores_gemma":[0.004397233,0.98236,0.01101661,0.0005346902,0.0006719155,0.00002392463,0.000102422,0.00005224932,0.0008409619],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004087648,"threshold_uncertainty_score":0.01367456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03151821235973624,"score_gpt":0.2989018197643072,"score_spread":0.267383607404571,"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."}}