{"id":"W2121884091","doi":"10.1109/aps.2000.873728","title":"An efficient method for frequency-domain and transient analysis of interconnect networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Padé approximant; Moment (physics); Frequency domain; Lossy compression; Interconnection; Computer science; Transfer function; Time domain; Algorithm; Method of moments (probability theory); Matching (statistics); Point set registration; Transient (computer programming); Transmission line; Point (geometry); Topology (electrical circuits); Mathematics; Mathematical analysis; Telecommunications; Engineering; Physics","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":[0.0003687019,0.0007743333,0.0005912356,0.0008920629,0.0004739494,0.0005110063,0.001316946,0.0008703002,0.006575624],"category_scores_gemma":[0.001116128,0.0003866513,0.0005804548,0.0007878908,0.0003809033,0.0009001048,0.0006686109,0.0009865703,0.002628701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003953211,"about_ca_system_score_gemma":0.0008139012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00145985,"about_ca_topic_score_gemma":0.002117518,"domain_scores_codex":[0.999777,0.00003775269,0.000008599973,0.00002374094,0.0001333686,0.00001955795],"domain_scores_gemma":[0.9996442,0.0001451915,0.00002498864,0.00005496015,0.0001141751,0.0000165425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001033558,0.0000904608,0.0003769488,0.0003464332,0.00006026988,0.0002387372,0.0001449133,0.2530098,0.07012616,0.06994024,0.01189635,0.5936663],"study_design_scores_gemma":[0.00002515992,0.00002558371,0.0001041556,0.0000142465,0.000008657865,0.0001434688,0.00000958959,0.973296,0.006449513,0.006774978,0.01312925,0.0000192448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000566341,0.00004144719,0.998359,0.0000177021,0.0000191586,0.00001876213,0.00002012777,0.0004276293,0.0005297866],"genre_scores_gemma":[0.02955659,0.0001376687,0.9658875,0.00003336038,0.00003428971,0.0002201386,0.0001187267,0.000229143,0.00378256],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006575624,"threshold_uncertainty_score":0.02199763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01018787780535895,"score_gpt":0.2319177912146355,"score_spread":0.2217299134092765,"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."}}