{"id":"W3193125300","doi":"10.36227/techrxiv.15048117.v1","title":"Accelerated IE-GSTC Solver for Large-Scale Metasurface Field Scattering Problems using Fast Multipole Method (FMM)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Antenna and Metasurface Technologies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Ministère de la Défense Nationale","keywords":"Solver; Fast multipole method; Multipole expansion; Computation; Scattering; Computational science; Field (mathematics); Physics; Computer science; Algorithm; Electromagnetic field; Computational physics; Mathematics; Optics; Mathematical optimization; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003295336,0.00058589,0.0005001444,0.0003377981,0.0003078156,0.0006004237,0.0007974754,0.001163361,0.002959495],"category_scores_gemma":[0.0009959509,0.0002825212,0.0006247102,0.0003935906,0.0003963012,0.0005980486,0.000827339,0.001098648,0.0006398473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003975599,"about_ca_system_score_gemma":0.001131529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002314939,"about_ca_topic_score_gemma":0.002295513,"domain_scores_codex":[0.9998589,0.00002513255,0.000005959958,0.00001342712,0.00007993325,0.00001664132],"domain_scores_gemma":[0.9995982,0.0001690717,0.00003438508,0.00005422306,0.000120682,0.00002336642],"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":[0.00007403683,0.00006883769,0.001226316,0.0002897274,0.00005234289,0.0004620141,0.0002944883,0.793055,0.04422974,0.0702434,0.00536517,0.08463892],"study_design_scores_gemma":[0.000009586988,0.00000713902,0.00005342482,0.000006009656,0.000002191291,0.00005239864,0.00001249322,0.9931898,0.002254661,0.002233945,0.002174283,0.000004010747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009930963,0.000108605,0.9849119,0.0001289811,0.00003576058,0.00003399602,0.00005800034,0.0004055346,0.004386295],"genre_scores_gemma":[0.1666669,0.0002600751,0.8259273,0.0001266068,0.00005132251,0.0001889975,0.0002267528,0.0003066926,0.006245398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002959495,"threshold_uncertainty_score":0.009900451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06167040853332112,"score_gpt":0.3199976836536439,"score_spread":0.2583272751203228,"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."}}