{"id":"W2105163139","doi":"10.1049/iet-map:20070227","title":"Reducing computational costs using a multi-region finite element method for electromagnetic scattering","year":2008,"lang":"en","type":"article","venue":"IET Microwaves Antennas & Propagation","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Finite element method; Scattering; Boundary (topology); Boundary value problem; Domain (mathematical analysis); Set (abstract data type); Computational electromagnetics; Mathematical optimization; Computer science; Algorithm; Space (punctuation); Mathematics; Mathematical analysis; Applied mathematics; Computational science; Physics; Electromagnetic field; 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":[0.0009515424,0.0006404357,0.0008897726,0.0007002178,0.0004566965,0.0006721129,0.001561164,0.001211796,0.005549141],"category_scores_gemma":[0.002563515,0.00042013,0.0008038381,0.0006046518,0.0003349648,0.00129201,0.001100919,0.00115438,0.002085401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003203142,"about_ca_system_score_gemma":0.0009205614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001772842,"about_ca_topic_score_gemma":0.00280704,"domain_scores_codex":[0.9993632,0.0002091793,0.00003328297,0.00005826581,0.0003018975,0.00003425875],"domain_scores_gemma":[0.9986371,0.0008120738,0.00007178097,0.0001778961,0.0002659245,0.0000351686],"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":[0.0001754404,0.0001613507,0.000622006,0.0002668481,0.00007569303,0.0001611452,0.000206739,0.7217703,0.04590871,0.02357084,0.002479907,0.204601],"study_design_scores_gemma":[0.00001043154,0.00002283352,0.00004995392,0.00001138142,0.000007073124,0.00004541919,0.0000116099,0.9920826,0.003454141,0.001552811,0.002742263,0.000009452763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003180446,0.00006426498,0.9951611,0.00004161858,0.00001996573,0.00002060847,0.00001678412,0.0003398112,0.001155422],"genre_scores_gemma":[0.04073913,0.0000991139,0.9571902,0.00003580662,0.00001310522,0.0000991277,0.00005412251,0.000161263,0.001608222],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005549141,"threshold_uncertainty_score":0.01856369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02591216661483152,"score_gpt":0.2840454708938356,"score_spread":0.258133304279004,"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."}}