{"id":"W2104024997","doi":"10.5555/789083.1022858","title":"Transistor-Level Static Timing Analysis by Piecewise Quadratic Waveform Matching","year":2003,"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 Toronto","funders":"","keywords":"Waveform; Spice; Static timing analysis; Electronic circuit; Piecewise linear function; Electronic engineering; Piecewise; Very-large-scale integration; Transistor; Computer science; Quadratic equation; Time domain; CMOS; Integrated circuit; Control theory (sociology); Algorithm; Mathematics; Voltage; Electrical engineering; Engineering; Mathematical analysis","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":[0.0002544684,0.0003244352,0.0002459909,0.0005058954,0.0001725928,0.0003607081,0.0005886497,0.0002536623,0.002580579],"category_scores_gemma":[0.001187605,0.0001877715,0.0003360701,0.0005212114,0.0002241414,0.0008436362,0.0003413671,0.0004128318,0.0005628558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003741267,"about_ca_system_score_gemma":0.0004051684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001087143,"about_ca_topic_score_gemma":0.0008471831,"domain_scores_codex":[0.99985,0.00002398171,0.000006213927,0.0000163763,0.00008764894,0.00001583896],"domain_scores_gemma":[0.9998013,0.00007968495,0.00002419777,0.0000394145,0.00004949658,0.000005888926],"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":[0.00009544421,0.0000283484,0.0006351618,0.00008605725,0.00002240181,0.00009548225,0.00007796514,0.7268718,0.07093455,0.04573992,0.0008646369,0.1545482],"study_design_scores_gemma":[0.000002528269,0.00001557866,0.00007756815,0.000002222953,0.000002769826,0.00003114164,0.000003156382,0.9901007,0.005072932,0.003953695,0.0007348889,0.000002950557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0121919,0.00004282789,0.9856107,0.00002456713,0.000006652976,0.000009875755,0.00002107603,0.000497407,0.001595147],"genre_scores_gemma":[0.7207561,0.0002470105,0.2738362,0.00003830539,0.00002387212,0.00006116789,0.0001262052,0.0002471666,0.004664067],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002580579,"threshold_uncertainty_score":0.008632898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01642919589729326,"score_gpt":0.2067312719229495,"score_spread":0.1903020760256562,"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."}}