{"id":"W4402979814","doi":"10.1109/ap-s/inc-usnc-ursi52054.2024.10686124","title":"FDTD-Equivalent Neural Network Model for Electromagnetic Simulations","year":2024,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Finite-difference time-domain method; Computer science; Artificial neural network; Electromagnetic simulation; Computational electromagnetics; Electromagnetic field; Electronic engineering; Artificial intelligence; Physics; Engineering; Optics","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":[0.0001965678,0.0005329819,0.0003859721,0.0003437028,0.0002706974,0.0005088976,0.001325709,0.001147885,0.0058581],"category_scores_gemma":[0.0008088891,0.00030237,0.0005202028,0.0004254283,0.0003111164,0.0007440691,0.0005901291,0.0008630254,0.001466662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008103951,"about_ca_system_score_gemma":0.0006857609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005279283,"about_ca_topic_score_gemma":0.005418084,"domain_scores_codex":[0.9998481,0.00002684536,0.000007002449,0.00002142016,0.00008202232,0.00001458606],"domain_scores_gemma":[0.9998367,0.00006243293,0.00001628025,0.00002193862,0.00005414255,0.000008455286],"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":[0.00003270912,0.00002909049,0.0003557885,0.000103686,0.00002358992,0.0001336109,0.00004858656,0.9266053,0.007231059,0.04233178,0.003799776,0.01930506],"study_design_scores_gemma":[0.000002528406,0.000002680741,0.00002720948,0.000004033667,0.000001615823,0.00001745106,0.000002616155,0.9942572,0.0004964551,0.002002028,0.00318377,0.000002390343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004619117,0.0003031075,0.9694472,0.0002651986,0.0001234999,0.00005267034,0.0004231726,0.0005431766,0.0242229],"genre_scores_gemma":[0.4260387,0.001436653,0.4999814,0.0005592326,0.0001231996,0.0007545275,0.001503292,0.0005897361,0.0690132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0058581,"threshold_uncertainty_score":0.01959729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02773133544323066,"score_gpt":0.3028123124103736,"score_spread":0.275080976967143,"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."}}