{"id":"W114882391","doi":"","title":"Dynamic global resource allocation in shared data centers and clouds","year":2012,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Cache; Allocator; Cloud computing; Quality of service; Resource allocation; Distributed computing; Memory hierarchy; Resource (disambiguation); Resource management (computing); Key (lock); Computer network; Database; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.001529423,0.0001498081,0.0002459424,0.00008551714,0.0003140303,0.0000744948,0.001586275,0.00003634993,7.440763e-7],"category_scores_gemma":[0.001205752,0.0001066601,0.0000266087,0.001220565,0.0003071337,0.0001131544,0.002599047,0.000172675,0.000001881075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002883346,"about_ca_system_score_gemma":0.0001060165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007539353,"about_ca_topic_score_gemma":0.0001686521,"domain_scores_codex":[0.9977966,0.0004218546,0.0002714091,0.0004793344,0.0004994347,0.0005313582],"domain_scores_gemma":[0.9975151,0.0005695025,0.0001427665,0.0009850324,0.0007063961,0.00008113391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001683771,0.002400498,0.02672514,0.001570083,0.001080468,0.00001019072,0.09199277,0.02413995,0.003293576,0.4150387,0.02836798,0.4036969],"study_design_scores_gemma":[0.009358997,0.001421822,0.04916284,0.004084694,0.0000655988,0.000004960892,0.1772576,0.628389,0.004947285,0.01697377,0.1068478,0.001485605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9301389,0.006593004,0.008932012,0.04605386,0.001264669,0.004209331,0.0003928948,0.0001000727,0.002315287],"genre_scores_gemma":[0.9964593,0.0001402936,0.00288406,0.00004937756,0.00002166202,0.00003179146,0.000007393034,0.000006173965,0.0003999176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6042491,"threshold_uncertainty_score":0.4349472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1086520384058891,"score_gpt":0.4004308103612403,"score_spread":0.2917787719553512,"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."}}