{"id":"W2921573433","doi":"10.1088/1361-6560/ab10b2","title":"Rigid-body motion correction in hybrid PET/MRI using spherical navigator echoes","year":2019,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Ottawa Mental Health Centre; Lawson Health Research Institute; Robarts Clinical Trials; Siemens (Canada); Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Siemens Healthineers","keywords":"Magnetic resonance imaging; Positron emission tomography; Motion (physics); Computer science; Computer vision; Real-time MRI; Artificial intelligence; Nuclear medicine; Medicine; Radiology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002262921,0.0001027696,0.0003197642,0.00005618924,0.00002030052,0.000002423828,0.00004748291,0.00004640217,0.00006924788],"category_scores_gemma":[0.00007426027,0.00007499098,0.00002248786,0.0002242595,0.0001727155,0.00003493112,0.00003217089,0.0003180066,0.000008233054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005427058,"about_ca_system_score_gemma":0.00002834253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004198068,"about_ca_topic_score_gemma":0.000003903431,"domain_scores_codex":[0.9992227,0.00004272008,0.0002342719,0.0002558467,0.00007174504,0.0001727066],"domain_scores_gemma":[0.9995884,0.00008969527,0.0000585078,0.0001593357,0.00003248276,0.00007159373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001439257,0.0006193817,0.52168,0.0002076806,0.00002935823,0.00005746416,0.0002927629,0.00003224339,0.4092802,0.007100753,0.005449444,0.05510682],"study_design_scores_gemma":[0.01311236,0.003341163,0.08563847,0.003776881,0.0002913264,0.001374597,0.00151767,0.729728,0.03782607,0.08268569,0.03955516,0.001152592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9730483,0.0000905228,0.02224527,0.003188955,0.0002643749,0.000338565,0.000001542044,0.0000454641,0.0007769543],"genre_scores_gemma":[0.9949971,0.0002098987,0.003412639,0.0009035224,0.0003387783,0.00001757678,0.00005548223,0.00000916889,0.0000558425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7296958,"threshold_uncertainty_score":0.3058043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1104700873729307,"score_gpt":0.4198109313824627,"score_spread":0.309340844009532,"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."}}