{"id":"W4283359293","doi":"10.1016/j.mri.2022.06.005","title":"Increased brain volumetric measurement precision from multi-site 3D T1-weighted 3 T magnetic resonance imaging by correcting geometric distortions","year":2022,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Ottawa Hospital; McGill University; University of Toronto; Montreal Neurological Institute and Hospital; Thunder Bay Regional Research Institute; Baycrest Hospital; Sunnybrook Health Science Centre; Western University","funders":"","keywords":"Scanner; Imaging phantom; Isocenter; Magnetic resonance imaging; Distortion (music); Standard deviation; Nuclear medicine; Physics; Mathematics; Computer science; Artificial intelligence; Medicine; Statistics; Radiology","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":[0.004429206,0.001487226,0.0008047759,0.001190453,0.000516245,0.002277441,0.001441165,0.001672433,0.002683058],"category_scores_gemma":[0.01950566,0.001364623,0.0006264541,0.0014897,0.0006748565,0.001658808,0.00121781,0.001321231,0.001014258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000682221,"about_ca_system_score_gemma":0.001101661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002804915,"about_ca_topic_score_gemma":0.006017792,"domain_scores_codex":[0.9975722,0.0006029822,0.0001792189,0.0006823582,0.0008687252,0.00009451751],"domain_scores_gemma":[0.9898358,0.004145015,0.001198096,0.002140992,0.002567312,0.0001128119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001118583,0.00009086313,0.01350113,0.001761387,0.000706259,0.0004721518,0.00126235,0.02969828,0.5610133,0.008644494,0.007434323,0.3742968],"study_design_scores_gemma":[0.0001559051,0.0005241245,0.06278796,0.0003336062,0.001551133,0.008252098,0.0003126758,0.1995433,0.6748489,0.01245481,0.03866196,0.0005735071],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06062319,0.002181418,0.9286206,0.0005340212,0.0005632322,0.00007553412,0.0004588899,0.004353268,0.00258979],"genre_scores_gemma":[0.3761283,0.0011711,0.6159451,0.0005900862,0.0001547707,0.000118214,0.0006143461,0.002787424,0.002490646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004429206,"threshold_uncertainty_score":0.02342415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01613205729488606,"score_gpt":0.2701302664726056,"score_spread":0.2539982091777196,"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."}}