{"id":"W2141663147","doi":"10.1109/22.971612","title":"Efficient sensitivity analysis of lossy multiconductor transmission lines with nonlinear terminations","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Microwave Theory and Techniques","topic":"Electromagnetic Compatibility and Noise Suppression","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Admittance; Sensitivity (control systems); Electric power transmission; Lossy compression; Transmission line; Admittance parameters; Nonlinear system; Electronic engineering; Topology (electrical circuits); Matrix (chemical analysis); Equivalent circuit; Transmission (telecommunications); Voltage; Mathematics; Computer science; Electrical impedance; Engineering; Physics; Materials science; Electrical engineering; Telecommunications","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":[0.0002927734,0.0001566234,0.0002469224,0.0003429696,0.00009921621,0.00001048301,0.00004515459,0.00008537388,0.00006889775],"category_scores_gemma":[0.000002742222,0.0001268938,0.00009582284,0.0004679064,0.0001251158,0.00003983586,7.119493e-7,0.0001776712,6.1121e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001908771,"about_ca_system_score_gemma":0.00000952998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001285942,"about_ca_topic_score_gemma":0.00005922879,"domain_scores_codex":[0.9992651,0.0001263334,0.0001971223,0.0001838971,0.00009199958,0.0001355176],"domain_scores_gemma":[0.9993821,0.0002677868,0.00002791976,0.0002086819,0.00005911598,0.00005435651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001875828,0.0002179074,0.00001411187,0.00004185612,0.0001572486,0.000005960124,0.000382666,0.01576227,0.9189216,0.00003938498,0.000001639864,0.06426771],"study_design_scores_gemma":[0.0001480844,0.0001854021,0.0001084073,0.00007935114,0.0004320119,0.0000187022,0.00004423971,0.04684063,0.951828,0.0001083668,0.00006068146,0.0001461085],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6129361,0.00004702138,0.3865434,0.00001282375,0.00001247526,0.0001257021,0.00002709858,0.000157188,0.0001382276],"genre_scores_gemma":[0.991591,0.0001394933,0.008153277,0.00001043119,0.000008255387,0.00001007546,0.000006141253,0.00001594885,0.00006538023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3786549,"threshold_uncertainty_score":0.5174578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006688747488583549,"score_gpt":0.2289801020279564,"score_spread":0.2222913545393728,"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."}}