{"id":"W2128264388","doi":"10.1145/1278480.1278563","title":"Using negative edge triggered ffs to reduce glitching power in FPGA circuits","year":2007,"lang":"en","type":"article","venue":"Proceedings - ACM IEEE Design Automation Conference","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Lookup table; Field-programmable gate array; Computer science; Electronic circuit; Dissipation; Signal edge; Routing (electronic design automation); Enhanced Data Rates for GSM Evolution; Logic gate; Power (physics); Electronic engineering; Macrocell array; Electrical engineering; Logic synthesis; Computer hardware; Engineering; Embedded system; Algorithm; Logic family; Physics; Telecommunications","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":[0.0001951191,0.0005971373,0.0003025084,0.0005438122,0.000292434,0.0003800535,0.0009393154,0.0002865774,0.001591636],"category_scores_gemma":[0.001053873,0.0002429184,0.0002693256,0.0002804093,0.0002210742,0.0007099535,0.0002561783,0.0003111704,0.0002394726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003145939,"about_ca_system_score_gemma":0.0003570525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001117515,"about_ca_topic_score_gemma":0.002540797,"domain_scores_codex":[0.9998285,0.0000235217,0.00001283542,0.00003654248,0.00007619876,0.00002245801],"domain_scores_gemma":[0.9994323,0.0002472764,0.00009857726,0.00009654216,0.0001078485,0.00001751563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006240515,0.0001624818,0.003637674,0.0001673806,0.00006599226,0.000396618,0.0001378247,0.2479381,0.1642468,0.007348039,0.001893174,0.573382],"study_design_scores_gemma":[0.00006346956,0.0006431907,0.002072846,0.00002749395,0.00007072018,0.0005468062,0.00003155162,0.84861,0.1381668,0.004886879,0.004843028,0.00003721173],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1359479,0.0003792376,0.8590826,0.00008885361,0.00005573856,0.00004998826,0.00004211582,0.002224348,0.002129313],"genre_scores_gemma":[0.7574157,0.0001748303,0.2395694,0.000118947,0.00002921392,0.00003678718,0.00007561554,0.0001326582,0.002446762],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001591636,"threshold_uncertainty_score":0.005324483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07454332034314884,"score_gpt":0.2971368018272829,"score_spread":0.222593481484134,"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."}}