{"id":"W2019828391","doi":"10.1109/tvlsi.2003.816139","title":"Low-leakage asymmetric-cell SRAM","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Leakage (economics); Static random-access memory; Leakage power; Sense amplifier; Degradation (telecommunications); Computer science; Electronic engineering; Transistor; Electrical engineering; Engineering; Semiconductor memory; Computer hardware; Voltage","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006144618,0.0005535858,0.0005191425,0.0008273274,0.0003404069,0.0002505005,0.0003136488,0.0004077979,0.0002689043],"category_scores_gemma":[0.00001354535,0.00053171,0.0002805584,0.001368165,0.00004803497,0.0008449867,0.000001048141,0.000781063,0.001843007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005098179,"about_ca_system_score_gemma":0.0000730124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000398356,"about_ca_topic_score_gemma":0.0001003606,"domain_scores_codex":[0.9970357,0.0002138989,0.0008425274,0.0005220466,0.0006499615,0.0007358011],"domain_scores_gemma":[0.99854,0.000161757,0.0001083919,0.0007521544,0.0001838434,0.0002538336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001082193,0.001911414,0.0001337078,0.0009977157,0.000378233,0.00005698477,0.002906579,0.8969299,0.06631158,0.001123649,0.01939228,0.009749786],"study_design_scores_gemma":[0.002075016,0.0003072796,0.00005359309,0.0003690975,0.0001157089,0.00006981706,0.001682589,0.2772976,0.6872496,0.00001895153,0.02959576,0.001165023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06539812,0.0003610571,0.9040891,0.00001521796,0.008318684,0.0008251905,0.0001471032,0.001048131,0.01979742],"genre_scores_gemma":[0.9944505,0.0001373097,0.000628509,0.00005995234,0.0001556118,0.0002875428,0.00002312824,0.0001426971,0.004114748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9290524,"threshold_uncertainty_score":0.9997134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006963472649608291,"score_gpt":0.1959009477767522,"score_spread":0.1889374751271439,"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."}}