{"id":"W1979834676","doi":"10.1118/1.4734850","title":"SU‐E‐J‐17: Evaluation of Metal Artifact Reduction in MVCTs Using a Model Based Image Reconstruction Method","year":2012,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Rod; Imaging phantom; Bremsstrahlung; Materials science; Iterative reconstruction; Optics; Attenuation; Detector; Projection (relational algebra); Cathode ray; Physics; Photon; Electron; Mathematics; Computer science; Nuclear physics; Algorithm; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001060667,0.0001056082,0.0001760742,0.00006056608,0.0000250615,0.000005365066,0.00004986837,0.00006748095,0.00006022453],"category_scores_gemma":[0.0001309017,0.0001092049,0.00005272444,0.0002304271,0.00005062801,0.0005647,0.00001039262,0.0002190267,0.000003209392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000146194,"about_ca_system_score_gemma":0.00006976609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008798464,"about_ca_topic_score_gemma":8.641267e-7,"domain_scores_codex":[0.9988391,0.000086192,0.0002469629,0.0001062675,0.0005081809,0.0002132422],"domain_scores_gemma":[0.9996276,0.00003983215,0.00005379791,0.0001251291,0.00006998946,0.00008363877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008547356,0.00006881588,0.0001722172,0.00004952068,0.00001622164,2.851623e-7,0.0002648963,0.6412303,0.1291881,0.0001123811,0.000008395012,0.2288804],"study_design_scores_gemma":[0.0003341056,0.000003748342,0.0001027896,0.00005518665,0.00005305477,0.000006734376,0.00005179393,0.827121,0.1683991,0.003780063,0.000003504207,0.00008890448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3631647,0.00007199776,0.6360763,0.00001172688,0.0002238559,0.00008004979,0.000001535527,0.00003752705,0.0003322768],"genre_scores_gemma":[0.933684,0.00000385198,0.0660544,0.00001123054,0.0002065663,0.00001066088,0.000008617561,0.00001862529,0.000002054059],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5705193,"threshold_uncertainty_score":0.4453247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05154369082923786,"score_gpt":0.3432631273043119,"score_spread":0.291719436475074,"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."}}