{"id":"W2132684735","doi":"10.1109/mwsym.1993.276723","title":"Two-dimensional transmission line matrix (TLM) simulation of the electromagnetic fields in a rectangular section of a discretized GaAs MESFET channel with arbitrary doping profile","year":2002,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"MESFET; Discretization; Channel (broadcasting); Electromagnetic field; Transmission line; Physics; Electronic engineering; Transmission-line matrix method; Matrix (chemical analysis); Mathematical analysis; Topology (electrical circuits); Computational physics; Electrical engineering; Materials science; Mathematics; Field-effect transistor; Engineering; Voltage; Computational electromagnetics; Transistor; Quantum mechanics; Composite material","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":[0.0001531863,0.0001459632,0.0002484632,0.0001248651,0.00002921747,0.000004997965,0.00008049739,0.00009665421,0.0005328482],"category_scores_gemma":[0.00003201856,0.00009926605,0.00007271671,0.0006601674,0.00003062088,0.0000641506,0.000009364258,0.0002197772,7.628222e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003185794,"about_ca_system_score_gemma":0.00001138266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004329899,"about_ca_topic_score_gemma":0.00001557612,"domain_scores_codex":[0.9989058,0.0001288307,0.0003789037,0.0001563613,0.0002370292,0.0001930852],"domain_scores_gemma":[0.9994646,0.0002195065,0.00006514318,0.0001645811,0.0000447652,0.00004135649],"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":[0.0001370335,0.00007598553,0.00008220618,0.0001093165,0.00001742696,0.000001112202,0.0002859538,0.8336435,0.1625923,0.00005370479,0.00001826958,0.002983204],"study_design_scores_gemma":[0.001186265,0.000504054,0.001244958,0.0001202857,0.0000243602,0.000005960263,0.000009688008,0.9231394,0.07321604,0.0004157723,0.00001195132,0.0001212518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9345849,0.000671198,0.06072042,0.0002097608,0.00007726349,0.0005414651,0.000001923401,0.0000997642,0.003093293],"genre_scores_gemma":[0.9825389,0.00001765839,0.01707459,0.00002848211,0.0000330511,0.00001603078,0.000004011918,0.00002235664,0.0002648589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0894959,"threshold_uncertainty_score":0.5834314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01119094941321399,"score_gpt":0.2509345223845311,"score_spread":0.2397435729713171,"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."}}