{"id":"W4395662114","doi":"10.23919/eucap60739.2024.10501632","title":"3D Method-of-Moment Design of Huygens' Metasurfaces","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Antenna and Metasurface Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Electrical impedance; Dielectric; Lossless compression; Moment (physics); Method of moments (probability theory); Electromagnetics; Electromagnetic field; Physics; Acoustics; Mathematical analysis; Optics; Computer science; Mathematics; Classical mechanics; Optoelectronics; Algorithm","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":[0.000249142,0.0004632721,0.0003849429,0.0002875326,0.0001987578,0.0005112737,0.0005833357,0.0006850884,0.002794516],"category_scores_gemma":[0.0004183171,0.0002886282,0.0004812011,0.0002355936,0.0002626314,0.0003214929,0.0004963081,0.0003827521,0.0009200918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003734596,"about_ca_system_score_gemma":0.0004178787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004207763,"about_ca_topic_score_gemma":0.0004483079,"domain_scores_codex":[0.9998423,0.00003357039,0.000005144447,0.00001617259,0.00008707489,0.00001563979],"domain_scores_gemma":[0.9998647,0.00003783999,0.00002065772,0.00001863558,0.00004737524,0.00001084676],"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":[0.000211456,0.00008143357,0.001033723,0.0002742398,0.00007255642,0.0003510083,0.0002992907,0.5609657,0.1510831,0.1189289,0.0052429,0.1614556],"study_design_scores_gemma":[0.00001782153,0.00006835172,0.0002039411,0.00001266602,0.000007647825,0.0001429732,0.00002394235,0.964715,0.0168877,0.005116984,0.01278361,0.00001930711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00918871,0.00007930169,0.9841343,0.00007353412,0.00003730709,0.00003430116,0.00004976583,0.0003273468,0.006075513],"genre_scores_gemma":[0.3134961,0.0001821553,0.6788524,0.0001104324,0.00003039654,0.0002343451,0.0001430204,0.0002161791,0.006734969],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002794516,"threshold_uncertainty_score":0.009348571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03386048967116791,"score_gpt":0.2898123352691991,"score_spread":0.2559518455980312,"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."}}