{"id":"W2047021873","doi":"10.1259/bjr/27295679","title":"Assessing the image quality of pelvic MR images acquired with a flat couch for radiotherapy treatment planning","year":2011,"lang":"en","type":"article","venue":"British Journal of Radiology","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University","keywords":"Scanner; Imaging phantom; Medicine; Image quality; Nuclear medicine; Radiation treatment planning; Image noise; Radiology; Radiation therapy; Artificial intelligence; Image (mathematics); Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001506434,0.0003624876,0.0002392811,0.001053821,0.0001719714,0.0004783803,0.0003488918,0.0006711317,0.002677607],"category_scores_gemma":[0.006784385,0.0003165401,0.0002926619,0.0004922337,0.0002763723,0.0003816701,0.000418098,0.0002891347,0.0004002498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002637171,"about_ca_system_score_gemma":0.0002687151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008421419,"about_ca_topic_score_gemma":0.001275736,"domain_scores_codex":[0.9991969,0.000362775,0.00008335602,0.0001023452,0.0001868519,0.0000676247],"domain_scores_gemma":[0.9973158,0.001088673,0.0004301024,0.0002091597,0.0007652137,0.0001910504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.006455458,0.0005066652,0.1876092,0.0006629944,0.0003831736,0.001553383,0.0007932984,0.003987032,0.6912581,0.0001484349,0.0007655678,0.1058767],"study_design_scores_gemma":[0.0001993932,0.007510002,0.784097,0.00006396664,0.000525681,0.01078258,0.0003639328,0.01523612,0.1793853,0.0001056092,0.001641349,0.00008899584],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764424,0.0008770996,0.02099923,0.0001087122,0.0000161747,0.0001589177,0.0001760449,0.0002033811,0.001017938],"genre_scores_gemma":[0.9801089,0.0002390754,0.01881811,0.00005824989,0.00001518635,0.00004820265,0.0002577968,0.00005071545,0.0004037618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002677607,"threshold_uncertainty_score":0.008957505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04026083701248549,"score_gpt":0.3574081688653131,"score_spread":0.3171473318528276,"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."}}