{"id":"W1995973104","doi":"10.1109/mwsym.2014.6848540","title":"A multi-resolution FDTD method for uncertainty quantification in the time-domain modeling of microwave structures","year":2014,"lang":"en","type":"article","venue":"","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Finite-difference time-domain method; Robustness (evolution); Polynomial chaos; Computer science; Algorithm; Grid; Uncertainty quantification; Microwave imaging; Monte Carlo method; Sparse grid; Wavelet; Microwave; Computational science; Mathematics; Optics; Artificial intelligence; Physics; Machine learning; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007996134,0.00009363783,0.0002048192,0.0001401481,0.00006701013,0.00004772937,0.0004903222,0.00007230959,0.00001356328],"category_scores_gemma":[0.003533675,0.00005033631,0.00008133931,0.000317254,0.00003836276,0.00006772639,0.0000248363,0.00007030394,0.000009243091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002231504,"about_ca_system_score_gemma":0.00003029866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008702948,"about_ca_topic_score_gemma":0.00006507523,"domain_scores_codex":[0.9983014,0.0003792519,0.0005169319,0.0002819404,0.000363268,0.0001572414],"domain_scores_gemma":[0.9968988,0.002329546,0.0001203701,0.0004284646,0.00019874,0.00002408877],"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":[0.00002404184,0.00002129186,0.000007790604,0.000007006257,0.000003415932,4.147633e-8,0.0004859309,0.9307377,0.01204285,0.05113849,0.0004076087,0.005123827],"study_design_scores_gemma":[0.0002530772,0.0000240181,0.0001114922,0.000006607905,0.000005491289,0.000001260395,0.0003466326,0.8662804,0.0003093403,0.1323098,0.0002900651,0.00006180297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002895155,0.00004125903,0.9959543,0.0003446341,0.00007413369,0.0003730449,0.000006388511,0.00001651002,0.0002945745],"genre_scores_gemma":[0.4983935,5.702932e-7,0.5014215,0.00004396742,0.00001958993,0.00001616457,0.00000381973,0.000003859811,0.00009705884],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4954984,"threshold_uncertainty_score":0.4230395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1212125312571866,"score_gpt":0.3719642011458725,"score_spread":0.2507516698886859,"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."}}