{"id":"W2004261580","doi":"10.1145/2463676.2467801","title":"Workload management for big data analytics","year":2013,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Workload; Analytics; Computer science; Citation; Big data; Data science; World Wide Web; Library science; Data mining; Operating system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002828391,0.001815408,0.0007811684,0.001368786,0.0007147109,0.00403839,0.001509889,0.001000711,0.01788876],"category_scores_gemma":[0.006114577,0.0008196434,0.0007382903,0.001507705,0.0004061052,0.004764172,0.00245889,0.002147226,0.007360974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001109147,"about_ca_system_score_gemma":0.001288591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00128573,"about_ca_topic_score_gemma":0.002253173,"domain_scores_codex":[0.9985922,0.0003967922,0.00009800884,0.0001505313,0.0006371311,0.0001253386],"domain_scores_gemma":[0.9971644,0.001183371,0.0001298478,0.0002691255,0.0008042814,0.0004489244],"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":[0.0001511296,0.0001518696,0.0007349689,0.000880531,0.00005370623,0.0001078623,0.0003879614,0.007623381,0.003644694,0.01889314,0.3805797,0.586791],"study_design_scores_gemma":[0.00006720953,0.000201616,0.002230071,0.001176927,0.00005251288,0.0004322351,0.0005707794,0.06791347,0.002397719,0.07735868,0.8475018,0.00009701561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009443949,0.1194073,0.7423947,0.02652488,0.01189462,0.0009231081,0.001795377,0.0122105,0.07540545],"genre_scores_gemma":[0.1506068,0.1680926,0.462746,0.007909805,0.03771901,0.001963018,0.009792558,0.005489432,0.155681],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01788876,"threshold_uncertainty_score":0.05984384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07476323072860164,"score_gpt":0.2620991339009233,"score_spread":0.1873359031723217,"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."}}