{"id":"W1981191435","doi":"10.1109/rtss.2013.44","title":"Worst Case Analysis of DRAM Latency in Multi-requestor Systems","year":2013,"lang":"en","type":"article","venue":"","topic":"Real-Time Systems Scheduling","field":"Computer Science","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Dram; Computer science; CAS latency; Memory controller; Latency (audio); Benchmark (surveying); Embedded system; Parallel computing; Registered memory; Distributed computing; Operating system; Computer hardware; Computer data storage; Semiconductor memory","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0005468043,0.0001392103,0.000450538,0.000682158,0.00003532435,0.0001868293,0.0005677686,0.00008511165,0.00004899066],"category_scores_gemma":[0.00005286882,0.0001128154,0.0001185818,0.002075719,0.00002469982,0.0008062214,0.0001361938,0.00009363629,0.000182256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007613845,"about_ca_system_score_gemma":0.00004329895,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05296575,"about_ca_topic_score_gemma":0.001078881,"domain_scores_codex":[0.9983202,0.0001336537,0.0006400745,0.0003840736,0.0002403634,0.0002816626],"domain_scores_gemma":[0.9985823,0.0001238754,0.0001965472,0.0008132643,0.0001694978,0.0001145319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001286735,0.001778737,0.5269204,0.0008937765,0.003517807,0.005645412,0.02258003,0.2116478,0.02396309,0.1816016,0.001139758,0.02029867],"study_design_scores_gemma":[0.000189416,0.0000192743,0.0118277,0.00003700452,0.00003627433,0.00009083722,0.0002660466,0.9871486,0.0001924114,0.0000294171,0.00001235464,0.0001506629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5279639,0.0001510006,0.4691274,0.00006323247,0.0002537066,0.0003714495,9.267677e-7,0.0001101195,0.001958261],"genre_scores_gemma":[0.9476269,0.000001868822,0.0514721,0.0000138177,0.00001499018,0.00004358322,0.00000113274,0.000007157105,0.0008184547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7755008,"threshold_uncertainty_score":0.9533406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03067242606097093,"score_gpt":0.2704592703814393,"score_spread":0.2397868443204684,"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."}}