{"id":"W2013715886","doi":"10.1016/j.jmr.2013.01.017","title":"Evaluation of B0-inhomogeneity correction for triple-quantum-filtered sodium MRI of the human brain at 4.7T","year":2013,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"University of Alberta; Alberta Innovates - Health Solutions; Heart and Stroke Foundation of Canada","keywords":"Voxel; SIGNAL (programming language); Nuclear magnetic resonance; Pulse (music); Magnetic resonance imaging; Pulse sequence; Offset (computer science); Signal-to-noise ratio (imaging); Physics; Algorithm; Optics; Computer science; Nuclear medicine; Artificial intelligence; 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":[0.001010012,0.00009033427,0.0002783939,0.00006142851,0.00007871888,0.000004552477,0.0001508722,0.00006424308,0.000175635],"category_scores_gemma":[0.0004496768,0.00006166624,0.0001821938,0.0001618889,0.00009844221,0.00006402789,0.00003138114,0.0001265719,0.000001241629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001177896,"about_ca_system_score_gemma":0.000118204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002264285,"about_ca_topic_score_gemma":0.00001312677,"domain_scores_codex":[0.9985002,0.00008178129,0.0006247258,0.0001105823,0.0005640687,0.0001186061],"domain_scores_gemma":[0.9974641,0.0001107313,0.0007882055,0.000301881,0.001285156,0.00004995292],"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":[0.0002374217,0.0003564032,0.002834254,0.00008265243,0.00001635451,4.570313e-7,0.0001848673,0.0001766123,0.7440169,0.0006408943,0.06505438,0.1863987],"study_design_scores_gemma":[0.006674491,0.003173078,0.4539888,0.0007204817,0.0005929301,0.000213074,0.0001650378,0.02724667,0.4327475,0.01723983,0.05703523,0.000202933],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785571,0.003122855,0.01250938,0.003227174,0.0002692723,0.001738104,0.0000142397,0.000009601977,0.0005522995],"genre_scores_gemma":[0.9894192,0.0001986071,0.007896344,0.0001165743,0.0001440505,0.0000961145,0.000002851345,0.00001520455,0.002111083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4511545,"threshold_uncertainty_score":0.2514676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0407298490030967,"score_gpt":0.3442551093744925,"score_spread":0.3035252603713958,"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."}}