{"id":"W1536272810","doi":"10.1109/cicc.2000.852717","title":"Multi-dimensional model reduction of VLSI interconnects","year":2002,"lang":"en","type":"article","venue":"","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Reduction (mathematics); Model order reduction; Very-large-scale integration; Computer science; Transformation (genetics); Electronic circuit; Congruence (geometry); Algorithm; Electronic engineering; Linear circuit; Equivalent circuit; Mathematics; Engineering; Electrical engineering; Embedded system; Voltage","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0000252793,0.00007024924,0.0000896125,0.00003220456,0.00003390593,0.00000560228,0.00004581792,0.00002104292,0.003090777],"category_scores_gemma":[8.051957e-7,0.00005947581,0.00006694721,0.00005854953,0.00002675448,0.00009138013,0.00001998109,0.00007566231,0.00004393416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004890187,"about_ca_system_score_gemma":0.000003968619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002329623,"about_ca_topic_score_gemma":3.629275e-7,"domain_scores_codex":[0.9995505,0.00001143166,0.0001386709,0.0001293431,0.00007127109,0.00009881906],"domain_scores_gemma":[0.9997592,0.000006433459,0.00004457074,0.0001058297,0.00003873268,0.00004522697],"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":[0.00004520121,0.001347881,0.0004924849,0.00001707567,0.000136853,6.453823e-7,0.0008355299,0.5870292,0.1889198,0.05831539,0.06363257,0.09922742],"study_design_scores_gemma":[0.0002592454,0.00001343316,0.00001335572,0.000007185866,0.000005624101,0.00000149769,0.000057979,0.9787977,0.01986254,0.0007640847,0.0001477457,0.00006964823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8766671,0.0000447859,0.09645556,0.0003826362,0.0003784051,0.0001303986,0.000005989081,0.00004857772,0.02588652],"genre_scores_gemma":[0.983244,0.000001969623,0.005766735,0.00002887936,0.0001176747,0.000004625088,0.000004998602,0.000006839836,0.0108243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3917685,"threshold_uncertainty_score":0.9978206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04417968439313003,"score_gpt":0.2541525083296034,"score_spread":0.2099728239364734,"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."}}