{"id":"W2886772604","doi":"10.1109/mwsym.2018.8439340","title":"Efficient Sensitivity Analysis of Microwave Structures with Multiple Design Parameters in FDTD","year":2018,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Finite-difference time-domain method; Electromagnetic field; Multiphysics; Field (mathematics); Microwave; Computer science; Bandwidth (computing); Finite difference method; Grid; Computational electromagnetics; Applied mathematics; Mathematics; Electronic engineering; Mathematical analysis; Finite element method; Physics; Optics; Engineering; Geometry; Telecommunications","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":[0.0005741436,0.000442025,0.0003812696,0.0004401424,0.0001976873,0.0005545047,0.0004805922,0.0005178852,0.0009375504],"category_scores_gemma":[0.002012476,0.0004404751,0.0003748962,0.000294157,0.0004703121,0.0005473102,0.0004880551,0.0003972104,0.0001641265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009137566,"about_ca_system_score_gemma":0.0004503334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002268062,"about_ca_topic_score_gemma":0.00152604,"domain_scores_codex":[0.9997144,0.00005914864,0.000008107363,0.000028092,0.0001654821,0.00002469327],"domain_scores_gemma":[0.9993076,0.0005003012,0.0000449489,0.00005810781,0.00007767147,0.00001134426],"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":[0.00004178603,0.0000221771,0.0006712249,0.00007972657,0.00002519084,0.0001245675,0.0000714105,0.9440214,0.0269109,0.01181049,0.0003625321,0.01585866],"study_design_scores_gemma":[0.000001724041,0.000005083034,0.0001085976,0.000003638135,0.000003087071,0.00001543772,0.000003518901,0.9948633,0.003565293,0.001090711,0.0003364994,0.000002961122],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06884125,0.0002488716,0.9244025,0.0001324015,0.00002791399,0.00004456259,0.00008011113,0.0003955298,0.005826789],"genre_scores_gemma":[0.8767536,0.0002425751,0.1199907,0.0000537818,0.00001327304,0.00007862976,0.00009962927,0.00008662729,0.002681106],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002268062,"threshold_uncertainty_score":0.006629765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01696846229111783,"score_gpt":0.2529254681232865,"score_spread":0.2359570058321687,"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."}}