{"id":"W2972899136","doi":"","title":"Perfect Electric Conductor Implementation in 3D Lebedev FDTD","year":2019,"lang":"en","type":"article","venue":"European Conference on Antennas and Propagation","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Perfect conductor; Finite-difference time-domain method; Conductor; Electric field; Grid; Anisotropy; Electrical conductor; Resonator; Computer science; Field (mathematics); Acoustics; Optics; Physics; Electrical engineering; Engineering; Mathematics; Geometry; Scattering","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":[0.0002972783,0.0001182914,0.0001224337,0.0001194915,0.00002647476,0.00005130086,0.00005303659,0.00002335679,0.0003985532],"category_scores_gemma":[0.00002054864,0.0001073041,0.00001660132,0.0002047205,0.00001068313,0.00009847258,0.000008571297,0.0001416515,0.0001429156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002671225,"about_ca_system_score_gemma":0.00001223673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008214331,"about_ca_topic_score_gemma":0.000005507249,"domain_scores_codex":[0.9991562,0.0001970611,0.0001965616,0.0001801446,0.00009800692,0.0001720263],"domain_scores_gemma":[0.9997432,0.00004530908,0.00003329321,0.00009827386,0.00003571154,0.00004416818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003993796,0.00002551738,0.00726801,0.00005769065,0.00001001031,0.000005356868,0.0004683128,0.0002246838,0.5062998,0.003536624,0.00005889786,0.4820051],"study_design_scores_gemma":[0.002554244,0.001727978,0.4873025,0.0001440286,0.00001459186,0.00001385993,0.0003374956,0.4818356,0.02210781,0.0005429859,0.002718823,0.0007001568],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9626762,0.0001114896,0.00227829,0.0001043906,0.0001296995,0.0003135838,0.000001275075,0.0001017481,0.03428337],"genre_scores_gemma":[0.9989633,0.000156671,0.0004842238,0.0001140371,0.00003116767,0.000005074312,0.00001450654,0.00002141019,0.0002095869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.484192,"threshold_uncertainty_score":0.4375734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02013249508543148,"score_gpt":0.2756452113399266,"score_spread":0.2555127162544951,"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."}}