{"id":"W2168322670","doi":"10.1109/mwscas.1995.510312","title":"Using Spice and behavioral synthesis tools to optimize ASICs' peak power consumption","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":"Carleton University","funders":"","keywords":"Spice; Power consumption; Application-specific integrated circuit; Computer science; Scheduling (production processes); Power (physics); Electronic engineering; Power optimization; Embedded system; Engineering","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":[0.00009896989,0.000190184,0.0001897279,0.0001278279,0.00006786158,0.0001237394,0.0001056463,0.00009262528,0.00178738],"category_scores_gemma":[0.00001960745,0.0001888257,0.00003451347,0.000135412,0.00002867177,0.0004931039,0.00003696051,0.0001088207,0.0004192425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008912032,"about_ca_system_score_gemma":0.000003376908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001624706,"about_ca_topic_score_gemma":0.000004556556,"domain_scores_codex":[0.999114,0.00001458585,0.0002051416,0.0002023647,0.0001554888,0.0003083827],"domain_scores_gemma":[0.9995148,0.00006070487,0.00001721201,0.0002419183,0.0000277869,0.0001375738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001202118,0.0008837978,0.03179855,0.0006571683,0.0004367294,0.0002655112,0.008857362,0.3018861,0.4675283,0.002363168,0.0398485,0.1453546],"study_design_scores_gemma":[0.002057448,0.0003721445,0.04452981,0.0004257871,0.0004474228,0.0002659152,0.0005149128,0.7811132,0.1549508,0.00002677287,0.01200464,0.003291126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762124,0.0001802185,0.01637494,0.00003886734,0.0003042245,0.0002425793,0.000009173748,0.0003935297,0.006244047],"genre_scores_gemma":[0.9650472,0.00007016576,0.03446041,0.00006355303,0.00003938356,0.00002011864,9.288967e-7,0.00004459952,0.0002536885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4792272,"threshold_uncertainty_score":0.9991251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09389346747886829,"score_gpt":0.2717512808012131,"score_spread":0.1778578133223448,"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."}}