{"id":"W2036013245","doi":"10.1016/j.prro.2014.12.006","title":"Turn down the noise—a blinded evaluation of iterative image reconstruction in radiation therapy computed tomography simulation","year":2015,"lang":"en","type":"article","venue":"Practical Radiation Oncology","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; McMaster University","funders":"","keywords":"Medicine; Iterative reconstruction; Rank correlation; Correlation; Spearman's rank correlation coefficient; Projection (relational algebra); Artificial intelligence; Noise (video); Nuclear medicine; Radiation treatment planning; Image noise; Tomography; Pairwise comparison; Medical imaging; Statistics; Radiation therapy; Radiology; Mathematics; Algorithm; Computer science; Image (mathematics); Geometry","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":[0.01988635,0.0008035129,0.0007569765,0.0006337804,0.0007939674,0.001863405,0.00138559,0.002539981,0.001966264],"category_scores_gemma":[0.1178756,0.0008269709,0.0006661717,0.0003203267,0.00142458,0.001309947,0.002016417,0.001220305,0.000346052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006662977,"about_ca_system_score_gemma":0.001530857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002430924,"about_ca_topic_score_gemma":0.002121601,"domain_scores_codex":[0.9904237,0.007175501,0.000491823,0.0006905461,0.001027878,0.0001904451],"domain_scores_gemma":[0.9027042,0.07727557,0.004333886,0.00666478,0.008002657,0.001018826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.06555923,0.002986946,0.03041838,0.001147834,0.001741036,0.0005728143,0.001856059,0.5285025,0.102575,0.007532624,0.002427734,0.2546799],"study_design_scores_gemma":[0.001896609,0.004979579,0.006994998,0.0001094631,0.0006186416,0.000561221,0.0001776184,0.9236041,0.05552267,0.003989875,0.00138506,0.0001601214],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6297012,0.0009122252,0.3646179,0.0004355452,0.0002318496,0.0005580125,0.0002774744,0.001139095,0.00212665],"genre_scores_gemma":[0.8900762,0.0001061733,0.1077859,0.0002258309,0.00004690425,0.0001922836,0.0002354142,0.0005174647,0.0008137816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01988635,"threshold_uncertainty_score":0.1051703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06123474879168304,"score_gpt":0.4296093717471706,"score_spread":0.3683746229554876,"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."}}