{"id":"W2890870026","doi":"10.1002/mrm.27411","title":"Multiband RF pulse design for realistic gradient performance","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Thomas Hospital","funders":"Centre For Medical Engineering, King’s College London; EPSRC Centre for Doctoral Training in Medical Imaging; King's College London; Imperial College London; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; Philips; Wellcome Trust; Medical Research Council; Wellcome","keywords":"Bandwidth (computing); Waveform; Computer science; Pulse (music); Radio frequency; Pulse-width modulation; Modulation (music); Distortion (music); Physics; Optics; Acoustics; Telecommunications; Amplifier; Voltage; Radar","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":[0.000445127,0.0004410862,0.0001753236,0.0002275227,0.000171409,0.0003276062,0.0002947404,0.0004409527,0.001782637],"category_scores_gemma":[0.001140224,0.0001874868,0.0001534795,0.0001802907,0.0002265275,0.0004766937,0.0002302012,0.0003629013,0.0005136957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003156713,"about_ca_system_score_gemma":0.0003361856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001797959,"about_ca_topic_score_gemma":0.0003119058,"domain_scores_codex":[0.9998757,0.00002756105,0.00001136225,0.00002452376,0.0000498064,0.00001114332],"domain_scores_gemma":[0.9994913,0.0001705796,0.0001068595,0.00006383361,0.0001436299,0.00002379167],"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":[0.0003049701,0.000116961,0.001116421,0.0005135825,0.00003769637,0.0001889772,0.0001887132,0.06389582,0.8477771,0.007995786,0.001052578,0.07681132],"study_design_scores_gemma":[0.00006789878,0.0006995341,0.001731372,0.00006504211,0.00006185439,0.0005462659,0.00003591295,0.2257952,0.751139,0.00289188,0.01692938,0.00003653222],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1176911,0.0008035292,0.87541,0.0002219084,0.00005213152,0.0001210703,0.00007690012,0.000556478,0.005066928],"genre_scores_gemma":[0.5932094,0.0004494912,0.403419,0.0001186727,0.00002654813,0.0001739652,0.0001056961,0.0001603845,0.002336849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001782637,"threshold_uncertainty_score":0.005963504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04922813410468031,"score_gpt":0.3453281526796624,"score_spread":0.2961000185749821,"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."}}