{"id":"W1559406793","doi":"10.1109/mwsym.1996.511205","title":"Improved excitation of 3D SCN TLM based on voltage sources","year":2002,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Natural Sciences and Engineering Research Council of Canada","funders":"University of Victoria","keywords":"Voltage; Excitation; Amplitude; Field (mathematics); Electric field; Physics; Electrical engineering; Electromagnetic field; Computer science; Electronic engineering; Optics; Engineering; Mathematics","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":[0.0001628642,0.0002227425,0.000214044,0.0001916168,0.0001300562,0.0003040907,0.0003503386,0.0003921664,0.001148485],"category_scores_gemma":[0.0002976978,0.0001416154,0.0001596088,0.0002570314,0.000274689,0.0002965955,0.0004667499,0.0002364095,0.0004463888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004955969,"about_ca_system_score_gemma":0.0002921252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006084086,"about_ca_topic_score_gemma":0.001272015,"domain_scores_codex":[0.9998755,0.00002431394,0.000004551155,0.00001030338,0.00007001162,0.00001532528],"domain_scores_gemma":[0.9998645,0.00004258327,0.00002324868,0.00002820661,0.00003098829,0.00001054279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001764529,0.00006028148,0.00102459,0.0002434137,0.00001286669,0.0004810119,0.00027664,0.167959,0.7277864,0.03229928,0.001948016,0.0677322],"study_design_scores_gemma":[0.00002792335,0.0001268258,0.0005631971,0.00003618156,0.000007415663,0.0002801771,0.00004091826,0.7433555,0.2412296,0.002868659,0.01143487,0.00002879984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2471451,0.0004524847,0.7212722,0.0002792052,0.0001195207,0.00006332792,0.000152373,0.001700062,0.02881563],"genre_scores_gemma":[0.789032,0.0002417227,0.2046016,0.00008689836,0.00001393032,0.00006011861,0.0001219499,0.0001175145,0.005724216],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001148485,"threshold_uncertainty_score":0.003842115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01523970693765071,"score_gpt":0.2390140119694971,"score_spread":0.2237743050318464,"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."}}