{"id":"W2131506286","doi":"10.1109/icecs.1996.582824","title":"Simulation of electromagnetic fields in guided wave structures using a quasi-network approach: the frequency-domain transmission line matrix method","year":2002,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Transmission-line matrix method; Transmission line; Planar; Frequency domain; Scattering parameters; Electromagnetic field; Electric power transmission; Transmission (telecommunications); Matrix (chemical analysis); Computer science; Electronic engineering; S-matrix theory; Field (mathematics); Scattering; Dispersion (optics); Method of moments (probability theory); Network analysis; Physics; Computational electromagnetics; Optics; Materials science; Engineering; Telecommunications; Electrical engineering; Mathematics","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":[0.0004813037,0.0001987164,0.0003102853,0.0001103563,0.0000535963,0.0000166673,0.0001371428,0.0001745855,0.0006853753],"category_scores_gemma":[0.00007909846,0.0001439001,0.00009315716,0.0007329918,0.00002935378,0.00005679028,0.00001078626,0.0002835435,9.380948e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004563581,"about_ca_system_score_gemma":0.000008174756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005496744,"about_ca_topic_score_gemma":0.000006214578,"domain_scores_codex":[0.9983321,0.0003598404,0.0005495838,0.0001987175,0.0002160604,0.0003437274],"domain_scores_gemma":[0.9988423,0.000751189,0.00006121179,0.0002484861,0.00003661891,0.00006018208],"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":[0.000009801194,0.00003072302,0.00002711271,0.00003890059,0.00001482931,0.000001224541,0.0004211475,0.9582495,0.0220206,0.001363886,0.00003472067,0.01778753],"study_design_scores_gemma":[0.000446534,0.0002005095,0.0002944432,0.0000153855,0.00002333302,0.000008707732,0.00002896537,0.9715223,0.001651262,0.02556864,0.000074324,0.0001656501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09914676,0.001261935,0.8953608,0.00008787129,0.00005573534,0.0003112851,6.115058e-7,0.00009554676,0.003679457],"genre_scores_gemma":[0.5245146,0.00002306248,0.4752978,0.00003817797,0.00005129608,0.000004518321,0.000001661822,0.00001808887,0.0000507511],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4253679,"threshold_uncertainty_score":0.7504379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0460696003670058,"score_gpt":0.3174194867808156,"score_spread":0.2713498864138097,"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."}}