{"id":"W2607674833","doi":"10.1109/hase.2017.16","title":"Acquisition of Virtual Machines for Tiered Applications with Availability Constraints","year":2017,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Virtual machine; Workload; Cloud computing; Server; Response time; Operating system; Task (project management); Distributed computing","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":[0.0002106983,0.00006182919,0.00009217526,0.00002539577,0.0002832223,0.00009157576,0.000654423,0.00001902249,0.00001217002],"category_scores_gemma":[0.00001362569,0.00004431965,0.00003569568,0.00003539042,0.0001800284,0.00002460771,0.0001918574,0.00002511965,0.000005716499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009315427,"about_ca_system_score_gemma":0.00001836364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002401776,"about_ca_topic_score_gemma":0.000007391579,"domain_scores_codex":[0.9994437,0.0000116329,0.0001211298,0.0002173035,0.0001059477,0.0001002712],"domain_scores_gemma":[0.9989164,0.00005568941,0.0001304367,0.0007839638,0.00008143457,0.00003210938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000237157,0.0002036671,0.00375125,0.00006351855,0.0000524978,6.699236e-7,0.0002401799,0.0009081013,0.0004478141,0.4553412,0.0007006651,0.5382668],"study_design_scores_gemma":[0.003030873,0.0009188475,0.08595493,0.00008685791,0.00005093748,0.00001519432,0.0001892621,0.8661302,0.005388099,0.02778872,0.009846567,0.0005994578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07277029,0.000004385819,0.9131327,0.0008926375,0.00004359753,0.0003643604,0.000004103487,0.00006853881,0.01271934],"genre_scores_gemma":[0.9537618,1.613818e-7,0.04527114,0.00005712097,0.00003481106,0.00003842014,0.000001312821,0.000002669575,0.0008325751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8809915,"threshold_uncertainty_score":0.2178345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01443699412552807,"score_gpt":0.2563082426416836,"score_spread":0.2418712485161555,"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."}}