{"id":"W2147061734","doi":"10.1109/clustr.2006.311844","title":"Autonomic Resource Management for a Cluster that Executes Batch Jobs","year":2006,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Provisioning; Server; Workload; Heuristic; Resource allocation; Distributed computing; Resource management (computing); Server farm; Cluster (spacecraft); Resource (disambiguation); Computer network; Cloud computing; Computer cluster; Operating system; Client–server model","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":[0.0004021144,0.0001889696,0.0001649271,0.0001435368,0.0002174193,0.0003084936,0.001027618,0.00004512378,0.00001158015],"category_scores_gemma":[0.000002563461,0.0001581745,0.0001431835,0.0001898552,0.0000282041,0.00003154513,0.0008226695,0.00006354325,0.00006986481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007425602,"about_ca_system_score_gemma":0.00000820027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009511685,"about_ca_topic_score_gemma":0.00001377435,"domain_scores_codex":[0.9984697,0.00003746608,0.0002448359,0.0005671938,0.000229137,0.0004516637],"domain_scores_gemma":[0.9989941,0.0001182727,0.00008114368,0.0007284639,0.0000202267,0.00005775631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002097633,0.0002195286,0.0008249339,0.0001020109,0.0001051543,0.00001624649,0.0003178552,0.04599756,0.00002017719,0.3492022,0.4729988,0.1301745],"study_design_scores_gemma":[0.0009597677,0.00006174287,0.006029253,0.00003048916,0.00002098705,0.000006816933,0.0001176435,0.3899207,0.0003447674,0.006946615,0.5952097,0.0003514503],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02829091,0.00008347702,0.7957908,0.006471877,0.0003039209,0.0006716487,8.968723e-7,0.0006731676,0.1677133],"genre_scores_gemma":[0.6873517,0.000002091423,0.1783577,0.003028688,0.0003556108,0.0001225762,0.000006401351,0.00003312025,0.1307421],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6590608,"threshold_uncertainty_score":0.6450168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0111571224137434,"score_gpt":0.2137989005388107,"score_spread":0.2026417781250673,"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."}}