{"id":"W2972504787","doi":"10.3233/jifs-190459","title":"Resource-utilization-aware task scheduling in cloud platform using three-way clustering","year":2019,"lang":"en","type":"article","venue":"Journal of Intelligent & Fuzzy Systems","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Cluster analysis; Computer science; CloudSim; Energy consumption; Cloud computing; Schedule; Data mining; Scheduling (production processes); Distributed computing; Artificial intelligence; Mathematical optimization; Mathematics","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":[0.001958175,0.0002592959,0.0005320662,0.0006311203,0.000126178,0.0003930902,0.001275348,0.0001210825,0.000006762393],"category_scores_gemma":[0.00005310907,0.0002160283,0.000215253,0.0007247633,0.00002393897,0.0001098029,0.0005047077,0.0004720778,0.00004646469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004211976,"about_ca_system_score_gemma":0.00009359878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001299376,"about_ca_topic_score_gemma":0.00002402059,"domain_scores_codex":[0.9968755,0.0001260929,0.001360109,0.0003548193,0.0008150845,0.0004684585],"domain_scores_gemma":[0.9979775,0.000172352,0.0009043904,0.0005629204,0.0002241872,0.0001586731],"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":[0.00002584248,0.00006573444,0.008027723,0.0001718507,0.00006379483,0.00006983814,0.001276646,0.9826668,0.0001593391,0.001404723,0.00007712736,0.005990584],"study_design_scores_gemma":[0.0003882778,0.0001626704,0.000350067,0.001696115,0.00001384209,0.0002711121,0.001729569,0.9900201,0.000147806,0.0001700523,0.004796634,0.0002537298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6048834,0.001138174,0.3901327,0.00009337987,0.002536525,0.0002665722,4.409197e-7,0.00003988652,0.0009089466],"genre_scores_gemma":[0.9961709,0.00001457879,0.002859065,0.00007174892,0.0006752654,0.000001493464,5.210625e-7,0.00002602291,0.0001803789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3912876,"threshold_uncertainty_score":0.8809378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04902137958512057,"score_gpt":0.2721995078721349,"score_spread":0.2231781282870144,"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."}}