{"id":"W2783145157","doi":"10.1007/s11227-017-2226-0","title":"Preemptive cloud resource allocation modeling of processing jobs","year":2018,"lang":"en","type":"article","venue":"The Journal of Supercomputing","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Cloud computing; Distributed computing; Scheduling (production processes); Quality of service; Cloud testing; Software deployment; Resource allocation; Workload; Job scheduler; Cloud computing security; Operating system; Computer network","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":[0.002956822,0.000139113,0.0002424175,0.000161742,0.0003640213,0.00008530291,0.001450198,0.00004344795,0.000001831272],"category_scores_gemma":[0.00009465111,0.00009233986,0.0001027799,0.0004877543,0.0001173152,0.00009360041,0.0005324203,0.0002842652,0.000003857182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005246097,"about_ca_system_score_gemma":0.0000761457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003291592,"about_ca_topic_score_gemma":0.000001680846,"domain_scores_codex":[0.9981009,0.0002445533,0.0006934981,0.0001611583,0.0005300894,0.0002698365],"domain_scores_gemma":[0.9983867,0.0001863082,0.000477444,0.0003690399,0.0005169316,0.00006362482],"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":[0.00006681456,0.0001357156,0.0004612201,0.00009453428,0.0001125599,0.000008416437,0.04445879,0.7675275,0.002657316,0.00251888,0.0005203816,0.1814378],"study_design_scores_gemma":[0.000258416,0.000231242,0.0002362363,0.0003983867,0.00003125979,0.0001161045,0.001568305,0.9948798,0.001127503,0.0007104904,0.0003345102,0.0001077498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5264653,0.0002785021,0.4715018,0.000691785,0.000185875,0.00005591339,6.610838e-8,0.00002681641,0.0007939246],"genre_scores_gemma":[0.9784098,0.000003865765,0.020392,0.0001527483,0.0009982805,1.768045e-7,1.045841e-7,0.00001162864,0.00003143245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4519445,"threshold_uncertainty_score":0.376551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02319223057667303,"score_gpt":0.2494204818584888,"score_spread":0.2262282512818158,"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."}}