{"id":"W1614260347","doi":"10.1109/iscas.2006.1692951","title":"Efficient Passive Transmission Line Macromodeling Algorithm using Method of Characteristics","year":2006,"lang":"en","type":"article","venue":"","topic":"Lightning and Electromagnetic Phenomena","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Passivity; Computer science; Transmission line; Lossy compression; Electric power transmission; Transmission (telecommunications); Algorithm; Macro; Line (geometry); Electronic engineering; Telecommunications; Mathematics; Electrical engineering; Engineering; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003465996,0.0006829238,0.0005030955,0.0004545217,0.0003541697,0.0005036439,0.0007986154,0.0005002684,0.002750507],"category_scores_gemma":[0.000859393,0.0003298976,0.0004059791,0.0003071264,0.0002360199,0.000798749,0.00034618,0.0007133003,0.0009883657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000476724,"about_ca_system_score_gemma":0.0006045901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001484711,"about_ca_topic_score_gemma":0.001490415,"domain_scores_codex":[0.9998792,0.00002815967,0.000004662998,0.00002557263,0.00005278095,0.000009512398],"domain_scores_gemma":[0.9997329,0.0001371112,0.00002508554,0.00003312634,0.00006331199,0.000008586776],"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":[0.00007236732,0.00003351467,0.0004975999,0.000131576,0.00003668611,0.00008034586,0.0001682076,0.7148687,0.02791103,0.04882814,0.001975998,0.2053958],"study_design_scores_gemma":[0.00001297145,0.00002026249,0.00004242441,0.000005987306,0.000007147521,0.00003339527,0.000008542919,0.9879148,0.00313876,0.004468567,0.004341192,0.000005850184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009348517,0.000009586899,0.9984295,0.000008163296,0.000003316856,0.000006851677,0.000007631667,0.0002433532,0.0003567871],"genre_scores_gemma":[0.1222274,0.0001032121,0.8746192,0.00002513729,0.00001379621,0.0001913819,0.0001472796,0.0003504231,0.002322159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002750507,"threshold_uncertainty_score":0.009201407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008386772178544779,"score_gpt":0.2526133578863652,"score_spread":0.2442265857078205,"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."}}