{"id":"W3181283944","doi":"10.1007/s10470-021-01907-x","title":"A 350 mV, 2 MHz, 16-kb SRAM with programmable wordline boosting in the 65 nm CMOS technology","year":2021,"lang":"en","type":"article","venue":"Analog Integrated Circuits and Signal Processing","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Boosting (machine learning); Static random-access memory; CMOS; Macro; Voltage; Energy consumption; Electronic engineering; Electrical engineering; Computer science; Engineering; Artificial intelligence","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":[0.0001462428,0.000274422,0.0003324543,0.0003137023,0.000311564,0.0005152055,0.0008742302,0.0004210205,0.003569747],"category_scores_gemma":[0.0002707511,0.0001961067,0.0001843713,0.0005101762,0.0001266531,0.0009424993,0.0003554176,0.0002794927,0.001361293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003441887,"about_ca_system_score_gemma":0.0007645586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001228885,"about_ca_topic_score_gemma":0.002871175,"domain_scores_codex":[0.9998192,0.00001866586,0.00001883222,0.00005186736,0.00006093984,0.00003052316],"domain_scores_gemma":[0.9998897,0.00001597519,0.00001745057,0.0000159329,0.00004226783,0.00001861058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001466552,0.0002640896,0.006389609,0.0008090553,0.0001385713,0.002457131,0.0003040089,0.006400317,0.7571086,0.01370257,0.02296099,0.1879985],"study_design_scores_gemma":[0.0005533851,0.00551805,0.01118617,0.0003309067,0.0006999301,0.008029339,0.0003418123,0.06111038,0.7035732,0.007260956,0.2011735,0.000222304],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7109302,0.01010928,0.1838771,0.002275739,0.00125205,0.0004449041,0.00273417,0.01355255,0.07482394],"genre_scores_gemma":[0.9296684,0.0009408633,0.05366414,0.0007159,0.0001117407,0.00005102894,0.0005579537,0.00009451985,0.01419549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003569747,"threshold_uncertainty_score":0.01194203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008744316537402406,"score_gpt":0.2018009106364207,"score_spread":0.1930565940990183,"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."}}