{"id":"W2893188751","doi":"10.1145/3267809.3267820","title":"Fast and Accurate Load Balancing for Geo-Distributed Storage Systems","year":2018,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Education, Audiovisual and Culture Executive Agency; Stiftelsen för Strategisk Forskning; European Commission","keywords":"Computer science; Workload; Latency (audio); Distributed computing; Load balancing (electrical power); Computer network; Distributed database; Operating system; Telecommunications","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":[0.0003968696,0.0001063003,0.0001269211,0.00003760784,0.0002307263,0.0003004479,0.0003834419,0.00003394974,0.000002568579],"category_scores_gemma":[0.00003044631,0.00008388277,0.00002951071,0.0001656988,0.00003696044,0.00001972893,0.0003640664,0.0000437707,0.00002264782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005026715,"about_ca_system_score_gemma":0.0000240162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008398064,"about_ca_topic_score_gemma":0.00000891797,"domain_scores_codex":[0.9990474,0.0000265159,0.0001588532,0.0003306644,0.0001635264,0.000273013],"domain_scores_gemma":[0.9993182,0.0000753874,0.00006534903,0.0003396139,0.000125005,0.00007642772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000114073,0.0004451915,0.002984958,0.001260877,0.0005759713,0.0001118778,0.01004148,0.1446631,0.002891941,0.3185498,0.2558877,0.262473],"study_design_scores_gemma":[0.0003083367,0.00009897076,0.0007824459,0.00003008205,0.00000487977,0.0000097684,0.0001164428,0.9770484,0.00008455237,0.000113752,0.02127009,0.0001323002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1167846,0.00009201521,0.879389,0.0004318322,0.0005467137,0.0002280343,0.000003928128,0.000252193,0.002271685],"genre_scores_gemma":[0.9915048,5.653225e-7,0.005971801,0.0001652112,0.0002823948,0.00001113544,0.000001404469,0.00000603145,0.002056647],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8747202,"threshold_uncertainty_score":0.342064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389888165704632,"score_gpt":0.2363140551788225,"score_spread":0.2224151735217762,"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."}}