{"id":"W1960108990","doi":"10.1002/mrm.25424","title":"Dual optimization method of radiofrequency and quasistatic field simulations for reduction of eddy currents generated on 7T radiofrequency coil shielding","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health","keywords":"Electromagnetic shielding; Eddy current; Electromagnetic coil; Reduction (mathematics); Nuclear magnetic resonance; Field (mathematics); Magnetic field; Dual (grammatical number); Materials science; Physics; Nuclear engineering; Mechanics; Acoustics; Electrical engineering; Mathematics; Engineering; Composite material","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":[0.0003181724,0.000520362,0.00039416,0.0003898805,0.0002129759,0.0002810822,0.0004687563,0.000586804,0.001886186],"category_scores_gemma":[0.0006129698,0.0002852086,0.0004621183,0.0002048683,0.0001983018,0.0002788494,0.0002433755,0.0002365261,0.0002765961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002421213,"about_ca_system_score_gemma":0.000566753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001608685,"about_ca_topic_score_gemma":0.002118114,"domain_scores_codex":[0.99992,0.00002825853,0.00000367988,0.00001031938,0.0000291257,0.000008644779],"domain_scores_gemma":[0.999817,0.00008060368,0.00002804551,0.0000132625,0.00005229951,0.00000882855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007600118,0.00006345306,0.000665645,0.0001197951,0.00004528381,0.00008485371,0.00006576475,0.9512035,0.01970885,0.002772185,0.0005510392,0.02464363],"study_design_scores_gemma":[0.00000721789,0.00001628051,0.00008084437,0.000002892372,0.000004714969,0.000009805225,0.000003988847,0.9981474,0.001147586,0.0001948246,0.0003817736,0.000002642533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06965397,0.0001545813,0.9246809,0.00008613466,0.0000401133,0.00008966313,0.00006444148,0.0004358576,0.004794342],"genre_scores_gemma":[0.5360229,0.0001495503,0.4593455,0.00006649569,0.00001764985,0.0003571109,0.0001225221,0.0002380538,0.003680191],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001886186,"threshold_uncertainty_score":0.006309927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03043235185504231,"score_gpt":0.3685163876127896,"score_spread":0.3380840357577473,"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."}}