{"id":"W4242355438","doi":"10.7873/date.2013.032","title":"A Dual Grain Hit-Miss Detector for Large Die-Stacked DRAM Caches","year":2013,"lang":"en","type":"article","venue":"Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE), 2013","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Dram; Static random-access memory; Cache; Computer science; Latency (audio); CAS latency; Embedded system; Computer hardware; CPU cache; Filter (signal processing); Energy consumption; Parallel computing; Operating system; Semiconductor memory; Electrical engineering; Engineering; Telecommunications; Memory controller","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","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001492726,0.000647105,0.0006054661,0.000611179,0.0004729293,0.001366091,0.001084688,0.0002709725,0.0005852414],"category_scores_gemma":[0.001798326,0.0006389286,0.0001858391,0.0009044048,0.0001250165,0.002208602,0.000322819,0.0004614051,0.00552087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001221171,"about_ca_system_score_gemma":0.0003238455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006228612,"about_ca_topic_score_gemma":0.001083489,"domain_scores_codex":[0.9950952,0.0007903122,0.00115505,0.001223353,0.0007047025,0.001031397],"domain_scores_gemma":[0.995364,0.000979442,0.0005862001,0.001335613,0.001381102,0.0003537145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002047495,0.003225368,0.003356296,0.0006179878,0.0002002614,0.00005339026,0.01283893,0.002056797,0.5428817,0.03502452,0.343393,0.05614699],"study_design_scores_gemma":[0.007473281,0.0007221983,0.02983944,0.001163585,0.0001223006,0.0001840993,0.0002439966,0.4368204,0.00531118,0.01004773,0.503778,0.004293793],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1598083,0.0001161149,0.833843,0.001999272,0.0005726003,0.00177196,0.0001403638,0.001142094,0.0006063684],"genre_scores_gemma":[0.9142399,0.0001294305,0.07379769,0.001009986,0.0002189744,0.0008457917,0.0009798333,0.0000980653,0.008680288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7600453,"threshold_uncertainty_score":0.9996706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06609829335444932,"score_gpt":0.2686641679908078,"score_spread":0.2025658746363584,"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."}}