{"id":"W2153798354","doi":"10.1109/iembs.2004.1403352","title":"Improving spatial signal homogeneity in MR 2D chemical shift imaging using outer volume saturation bands","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Voxel; Homogeneity (statistics); Saturation (graph theory); Nuclear magnetic resonance; Imaging phantom; Chemistry; Materials science; Analytical Chemistry (journal); Optics; Physics; Mathematics; Artificial intelligence; Computer science","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":[0.001747117,0.0008339304,0.0005851216,0.0009016013,0.0002780763,0.0007510741,0.0003352344,0.0006339402,0.0009515632],"category_scores_gemma":[0.003964147,0.000585136,0.0003505305,0.0005623617,0.00056691,0.001033111,0.0008425126,0.0004317852,0.0003035548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002091013,"about_ca_system_score_gemma":0.0002248413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000358054,"about_ca_topic_score_gemma":0.0005210432,"domain_scores_codex":[0.9991927,0.0003232645,0.00004824191,0.0001595959,0.0001953393,0.00008085937],"domain_scores_gemma":[0.9973149,0.001794423,0.0003230976,0.0002229674,0.0002787032,0.00006594841],"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":[0.0006563999,0.00004393899,0.001080384,0.0001230172,0.00005002051,0.0001526977,0.0001113368,0.002962541,0.9706955,0.0002346713,0.00007238209,0.02381711],"study_design_scores_gemma":[0.00005950496,0.001117513,0.01873164,0.00002064934,0.0002219645,0.001219814,0.00007688002,0.02083303,0.9540768,0.0007602798,0.002826654,0.00005520066],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.677143,0.002653714,0.3169375,0.0001723771,0.00003393542,0.00007901177,0.0001048712,0.0009620961,0.001913609],"genre_scores_gemma":[0.7984512,0.001589657,0.1977023,0.0001674475,0.00007448986,0.0001156884,0.0003306875,0.0005472244,0.001021158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001747117,"threshold_uncertainty_score":0.009239733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01317681124848107,"score_gpt":0.2929978706858588,"score_spread":0.2798210594373777,"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."}}