{"id":"W2278994996","doi":"10.1002/nbm.3454","title":"Volumetric navigated MEGA‐SPECIAL for real‐time motion and shim corrected GABA editing","year":2015,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Medical Research Council; National Institutes of Health","keywords":"Shim (computing); Subtraction; Imaging phantom; Computer science; Motion (physics); Rotation around a fixed axis; Artificial intelligence; Biomedical engineering; Physics; Nuclear magnetic resonance; Computer vision; Chemistry; Materials science; Nuclear medicine; Optics; Mathematics; Medicine","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":[0.000581994,0.0005993122,0.0002750965,0.0006476754,0.0002675568,0.0006238801,0.0007968905,0.0004628934,0.008203666],"category_scores_gemma":[0.001186165,0.0003949363,0.0002598758,0.0003427583,0.0002802633,0.00035814,0.0008986596,0.000536362,0.001122048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000192521,"about_ca_system_score_gemma":0.0006912036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006356291,"about_ca_topic_score_gemma":0.002101615,"domain_scores_codex":[0.9998899,0.00002447658,0.000007579614,0.00002272158,0.00003930886,0.00001594],"domain_scores_gemma":[0.9996542,0.0001201419,0.00004676445,0.00009164841,0.00005627598,0.00003103145],"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":[0.0004383646,0.00004463601,0.001057741,0.0003942652,0.0000618202,0.0004961101,0.0002709457,0.004489665,0.6486777,0.005419336,0.006217392,0.332432],"study_design_scores_gemma":[0.0001004098,0.0005777047,0.01273243,0.0001068059,0.0001327119,0.0123684,0.0001738204,0.1357085,0.7311929,0.005947005,0.1008089,0.0001504751],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05873566,0.0004008322,0.9325253,0.0001692579,0.00006083115,0.0001165921,0.0002468479,0.004458362,0.003286227],"genre_scores_gemma":[0.1633632,0.0003008014,0.8307869,0.0001068638,0.00002615079,0.0001676314,0.00037753,0.001227935,0.003642914],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008203666,"threshold_uncertainty_score":0.02744395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0315976615121947,"score_gpt":0.3412040829439502,"score_spread":0.3096064214317554,"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."}}