{"id":"W2170745653","doi":"10.1109/mwsym.2005.1517067","title":"Passive model order reduction for interconnect networks with large number of ports","year":2005,"lang":"en","type":"article","venue":"IEEE MTT-S International Microwave Symposium Digest, 2005.","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Reduction (mathematics); Interconnection; Computer science; Model order reduction; Parametric statistics; Order (exchange); Electronic engineering; Mathematical optimization; Algorithm; Mathematics; Telecommunications; Engineering","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":[0.0003629254,0.0006895284,0.0006680991,0.0003208071,0.0003699515,0.0004632361,0.0006470679,0.0005183208,0.001667446],"category_scores_gemma":[0.001151143,0.0003669632,0.0008563008,0.0002026422,0.0004991214,0.0008591028,0.0005540504,0.001168081,0.0005296902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003933085,"about_ca_system_score_gemma":0.0004686059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001177863,"about_ca_topic_score_gemma":0.001873696,"domain_scores_codex":[0.9997738,0.00007608386,0.000008969389,0.00002578745,0.0001011245,0.00001428246],"domain_scores_gemma":[0.9996645,0.0001781597,0.0000338698,0.00007616876,0.00004030294,0.000007069194],"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":[0.00004631365,0.00004603912,0.0003338561,0.0001250522,0.00003454247,0.0001331953,0.00009342963,0.8659548,0.01776448,0.06087875,0.001194299,0.05339526],"study_design_scores_gemma":[0.000003534841,0.00001429784,0.00002690351,0.000002970866,0.000004928164,0.00002124479,0.00000375413,0.9875063,0.001741546,0.009162014,0.001509032,0.000003539435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006971402,0.00008471909,0.9904818,0.00006807993,0.00001821061,0.00001637756,0.00001943066,0.0002925515,0.002047459],"genre_scores_gemma":[0.4050659,0.0005475968,0.5834981,0.0001180463,0.00007117493,0.0002674291,0.0002817388,0.0004055348,0.009744589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001667446,"threshold_uncertainty_score":0.00557816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008788701195204987,"score_gpt":0.2601535044315983,"score_spread":0.2513648032363933,"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."}}