{"id":"W1979154230","doi":"10.1139/p09-028","title":"Analysis of the complex effective permittivity of a heterogeneous sample by the finite-difference time-domain method","year":2009,"lang":"en","type":"article","venue":"Canadian Journal of Physics","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Permittivity; Finite-difference time-domain method; Reflectometry; Lossy compression; Physics; Binary number; Relative permittivity; Series (stratigraphy); Conductivity; Time domain; Mathematical analysis; Lossless compression; Function (biology); Statistical physics; Optics; Algorithm; Mathematics; Dielectric; Quantum mechanics; Statistics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000325854,0.0002259536,0.0002857211,0.0003782713,0.0001764994,0.0003168967,0.0004387934,0.0002988159,0.001049585],"category_scores_gemma":[0.001073164,0.0001249408,0.0002541765,0.0002894033,0.0003564165,0.0004836243,0.0001897161,0.0002855514,0.0002160209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003120165,"about_ca_system_score_gemma":0.0003979983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001232723,"about_ca_topic_score_gemma":0.0007506984,"domain_scores_codex":[0.999893,0.00001659978,0.000005249421,0.00001531199,0.00006145873,0.000008363851],"domain_scores_gemma":[0.9996657,0.0001877128,0.0000213572,0.00004089428,0.00007656723,0.000007668705],"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":[0.0001271926,0.00008543299,0.001398961,0.0002082586,0.00003846788,0.0001854002,0.0001341869,0.7171439,0.179337,0.02569897,0.0006310254,0.07501128],"study_design_scores_gemma":[0.000004130686,0.00001258809,0.0002178417,0.000002936647,0.000003867084,0.00005336828,0.000008550674,0.9854161,0.01274444,0.0008703234,0.0006603015,0.000005521367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05931647,0.000146584,0.9370078,0.00005340695,0.00002213324,0.00002441556,0.0000390829,0.0002765085,0.003113654],"genre_scores_gemma":[0.6383269,0.0002350327,0.3586699,0.00002950072,0.00001008549,0.00008228231,0.0001254242,0.00006512383,0.002455577],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001232723,"threshold_uncertainty_score":0.00351119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01345945816469259,"score_gpt":0.2625515477251685,"score_spread":0.2490920895604759,"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."}}