{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005832902,0.0003278042,0.000427619,0.0003125997,0.0007626074,0.0007877846,0.000589103,0.0003742431,0.0008312668],"category_scores_gemma":[0.0008539089,0.0001488053,0.0002273182,0.0004426752,0.0003616378,0.0006596297,0.0003131005,0.0003295703,0.0001380174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006667595,"about_ca_system_score_gemma":0.0009191149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002662505,"about_ca_topic_score_gemma":0.003791104,"domain_scores_codex":[0.999799,0.00004594044,0.00001018214,0.00004934545,0.00005602055,0.00003965075],"domain_scores_gemma":[0.9996933,0.0001208352,0.00004361849,0.00004681152,0.00004836598,0.00004709326],"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":[0.000323932,0.0001305728,0.003057512,0.0001206045,0.00005787688,0.0002255224,0.000103901,0.8218312,0.02462716,0.01410311,0.00353266,0.1318859],"study_design_scores_gemma":[0.00001763824,0.00006287355,0.0006934914,0.000003538444,0.00001378045,0.00004679715,0.00002735713,0.9911107,0.002552265,0.004262966,0.001200923,0.000007792736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2768026,0.0008655716,0.7138853,0.0004602018,0.0001037985,0.0001072156,0.00006688006,0.001501047,0.006207325],"genre_scores_gemma":[0.9226269,0.0002539711,0.07505818,0.0000390241,0.00004527116,0.00005680296,0.00007080761,0.00004872103,0.001800233],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002662505,"threshold_uncertainty_score":0.005293965,"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."}}