{"id":"W4241938333","doi":"10.32920/ryerson.14645178","title":"Performance-Oriented VM Provisioning in Clouds","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"Government of Ontario","keywords":"Provisioning; Bottleneck; Computer science; Cloud computing; Container (type theory); Virtual machine; Software deployment; Distributed computing; Workload; Replication (statistics); Response time; Operating system; Embedded system; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009775409,0.0006776949,0.0005744389,0.0005549904,0.0008261132,0.001630771,0.001267638,0.0009127193,0.001403881],"category_scores_gemma":[0.002007136,0.0004288715,0.0005071428,0.0008682643,0.0005259921,0.001254998,0.0009810639,0.0006931531,0.0003701254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001218622,"about_ca_system_score_gemma":0.001930093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006164833,"about_ca_topic_score_gemma":0.004751484,"domain_scores_codex":[0.9989531,0.0002891189,0.00004574591,0.0001465276,0.0002797371,0.0002857519],"domain_scores_gemma":[0.9994444,0.0001931615,0.0001044926,0.00008308068,0.0001049773,0.00006991086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001038196,0.00007816112,0.001059916,0.0001725813,0.00004187787,0.0001807162,0.00009545945,0.872403,0.007773558,0.01981211,0.002259728,0.09601913],"study_design_scores_gemma":[0.00001005293,0.00004125747,0.000412378,0.00002656565,0.00001509686,0.00007871208,0.00006804289,0.980532,0.003827842,0.01108286,0.003891579,0.00001362437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1221196,0.002858404,0.8556352,0.0008243929,0.0001851038,0.0002802738,0.000142439,0.001462699,0.01649198],"genre_scores_gemma":[0.8078371,0.0009904751,0.1884976,0.0001198129,0.00004284833,0.00007697238,0.00009712736,0.0001193393,0.00221865],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006164833,"threshold_uncertainty_score":0.01225787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01342825581755231,"score_gpt":0.2351811635976979,"score_spread":0.2217529077801456,"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."}}