{"id":"W2109705475","doi":"10.1109/mwsym.1990.99663","title":"S-parameters of microwave components computed with the 3D condensed symmetrical TLM node","year":2002,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Microstrip; Computation; Microwave; Node (physics); Band-pass filter; Filter (signal processing); Electronic circuit; Matrix (chemical analysis); Topology (electrical circuits); Transmission line; Filtering theory; Enhanced Data Rates for GSM Evolution; Computer science; Waveguide; Transmission-line matrix method; Electronic engineering; Algorithm; Physics; Electrical engineering; Engineering; Telecommunications; Acoustics; Computational electromagnetics; Optics; Materials science","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":[0.00007082556,0.0001082075,0.0001821648,0.0000714728,0.00002604818,0.0000122954,0.0001173694,0.00004363499,0.000220848],"category_scores_gemma":[0.00002062209,0.00006788341,0.00003895495,0.0004597051,0.00007054675,0.00001996885,0.00001238619,0.0001263188,0.00002706699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001748881,"about_ca_system_score_gemma":0.000001549979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009179829,"about_ca_topic_score_gemma":8.780335e-7,"domain_scores_codex":[0.9993384,0.00006491864,0.0001669626,0.0001005714,0.0001551691,0.000173954],"domain_scores_gemma":[0.9992344,0.0004782542,0.00002673059,0.0001677722,0.00003514066,0.0000576473],"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":[0.0001993234,0.0006646094,0.004918948,0.0001899874,0.0009167145,0.00003436408,0.00117172,0.237377,0.5264595,0.00200436,0.02978952,0.196274],"study_design_scores_gemma":[0.0007213982,0.0001527834,0.004951474,0.000007967665,0.00002230352,0.00001336336,0.00001090253,0.9759175,0.017474,0.00002895833,0.0005652996,0.0001340483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5966367,0.0002259547,0.3851336,0.0003795882,0.00008814374,0.0001937833,0.000001712055,0.0002001209,0.01714041],"genre_scores_gemma":[0.8951485,0.0000056617,0.1044335,0.0002309519,0.000008330884,0.000002437369,0.000001658544,0.00001500982,0.000153932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7385405,"threshold_uncertainty_score":0.2768205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02645900855290136,"score_gpt":0.2227508678520534,"score_spread":0.196291859299152,"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."}}