{"id":"W2970546348","doi":"10.14778/3342263.33422629","title":"DimmStore","year":2019,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Testbed; Server; Exploit; Locality; Power (physics); Memory management; Embedded system; Power consumption; Operating system; Computer network; Semiconductor memory","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":[0.0007098561,0.0008230429,0.0006363919,0.0008702517,0.0004452736,0.001419883,0.002479051,0.0007450805,0.1370349],"category_scores_gemma":[0.001787604,0.0004772327,0.0004217976,0.0008868331,0.0004260848,0.002084076,0.001905412,0.001223612,0.0421189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000710714,"about_ca_system_score_gemma":0.0006423022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008765967,"about_ca_topic_score_gemma":0.00162505,"domain_scores_codex":[0.9993193,0.00007990901,0.00003392786,0.0001502681,0.0003224073,0.00009416616],"domain_scores_gemma":[0.9991053,0.0001971397,0.00004860601,0.000301433,0.0002265574,0.0001210546],"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":[0.001866249,0.0003542581,0.003009226,0.0009035107,0.0001124122,0.0005093,0.0002762646,0.00565168,0.04777591,0.0192275,0.6237276,0.296586],"study_design_scores_gemma":[0.0005221894,0.0005856359,0.003368807,0.00007957333,0.00006118206,0.0007971844,0.0001029771,0.05423542,0.07815374,0.007185168,0.8548118,0.00009624104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07718886,0.004808824,0.1808141,0.00245218,0.001653108,0.001013738,0.02802155,0.3262075,0.3778403],"genre_scores_gemma":[0.4547762,0.002473816,0.1502106,0.002738397,0.0004686571,0.00124953,0.05292195,0.0219007,0.3132601],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1370349,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005575699143324562,"score_gpt":0.1855055953102538,"score_spread":0.1799298961669292,"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."}}