{"id":"W2020915215","doi":"10.1109/epep.2007.4387198","title":"Efficient Parameterized Nonlinear Simulation of VLSI Circuits using Domain Decomposition Techniques","year":2007,"lang":"en","type":"article","venue":"","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Very-large-scale integration; Parameterized complexity; Computer science; Electronic circuit; Nonlinear system; Integrated circuit; Domain (mathematical analysis); Electronic engineering; Algorithm; Mathematics; Engineering; Electrical engineering; Embedded system","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":[0.0001636611,0.00007745067,0.0001127252,0.0000622147,0.00005629714,0.00001079273,0.00003831722,0.00003222388,0.0001578931],"category_scores_gemma":[9.431551e-7,0.00006994257,0.0000681291,0.0001234086,0.00002538135,0.0000304874,0.00001334376,0.00005916912,0.000002201421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001535047,"about_ca_system_score_gemma":0.00000858182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002699077,"about_ca_topic_score_gemma":3.054034e-7,"domain_scores_codex":[0.9993926,0.00002134819,0.0002365917,0.0001200308,0.0001001577,0.0001293322],"domain_scores_gemma":[0.9996638,0.00004572389,0.00009801582,0.00009755851,0.00005356847,0.00004137944],"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":[0.00004589994,0.0002145259,0.0005082012,0.000007430144,0.00002180344,5.248438e-7,0.00008876246,0.6276854,0.2947604,0.002302791,0.000008079095,0.07435617],"study_design_scores_gemma":[0.0002114105,0.00002793708,0.000101034,0.00001818156,0.000009490579,6.974756e-7,0.00005291485,0.8363188,0.1624111,0.0006069775,0.0001495547,0.00009185648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5043063,0.000001892506,0.4941246,0.000005078376,0.00003868232,0.00009214638,0.000001681298,0.00002127866,0.001408325],"genre_scores_gemma":[0.9630354,1.704878e-7,0.0367383,0.00001882886,0.0001595474,0.000001517909,0.00001479697,0.000007891302,0.00002352367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4587291,"threshold_uncertainty_score":0.2852175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02514788800369161,"score_gpt":0.3290278112756457,"score_spread":0.3038799232719541,"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."}}