{"id":"W2021731414","doi":"10.1049/iet-cdt.2013.0109","title":"Column selection solutions for <i>L</i> 1 data caches implemented using eight‐transistor cells","year":2014,"lang":"en","type":"article","venue":"IET Computers & Digital Techniques","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Cache; Computer science; Overhead (engineering); Transistor; Static random-access memory; Dissipation; Scaling; Selection (genetic algorithm); CPU cache; Column (typography); Voltage; Computer hardware; Embedded system; Parallel computing; Electrical engineering; Computer network; Engineering; Artificial intelligence; Mathematics; Operating system; Physics","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"],"consensus_categories":[],"category_scores_codex":[0.0002544877,0.0002706241,0.0002658205,0.000170551,0.0002030427,0.0002752748,0.0005297955,0.0001090186,0.000003820582],"category_scores_gemma":[0.000009363917,0.0003022084,0.00008351426,0.0002695456,0.00005879289,0.001223614,0.0001362172,0.0001371602,0.00000768186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000195628,"about_ca_system_score_gemma":0.00003441996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003075149,"about_ca_topic_score_gemma":0.00001995008,"domain_scores_codex":[0.9985261,0.00001744686,0.0003610978,0.0003741143,0.0001738611,0.0005474102],"domain_scores_gemma":[0.9991494,0.00009351027,0.0000597458,0.0005215001,0.00008325409,0.00009253915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000060504,0.0002835351,0.0004316871,0.0005915395,0.0004197608,0.000003923205,0.0003828068,0.009438452,0.2189844,0.0008683674,0.5599821,0.208553],"study_design_scores_gemma":[0.0002780349,0.0001790294,0.00002618468,0.00007740808,0.0000456123,0.0000173969,0.000007224886,0.7015846,0.1003218,0.0002402943,0.19676,0.0004624284],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008640458,0.00004340798,0.9869434,0.00004789935,0.0004894314,0.0007049215,0.0003686773,0.002144477,0.0006173172],"genre_scores_gemma":[0.8613576,0.00002094894,0.1376665,0.00008503837,0.0002813703,0.00006449191,0.0004112654,0.00008966302,0.00002309604],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8527172,"threshold_uncertainty_score":0.999943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03887342976144327,"score_gpt":0.2441999563159854,"score_spread":0.2053265265545421,"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."}}