{"id":"W4229579902","doi":"10.1145/2637364.2592015","title":"Randomized routing schemes for large processor sharing systems with multiple service rates","year":2014,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Server; Routing (electronic design automation); Computer science; Distributed computing; Scheme (mathematics); Processor sharing; Exponential distribution; Homogeneous; Randomized algorithm; Computer network; Mathematics; Algorithm; Statistics; Queueing theory","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01718667,0.0003040996,0.0009322439,0.0004633857,0.0004632359,0.0002826422,0.000643968,0.00006176058,0.00006740124],"category_scores_gemma":[0.02677473,0.0002259836,0.0001503256,0.003462879,0.00002383853,0.001868126,0.0002089619,0.0001431272,0.0001253726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000715965,"about_ca_system_score_gemma":0.00003981856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001821695,"about_ca_topic_score_gemma":0.00001118704,"domain_scores_codex":[0.9974196,0.00009987329,0.0008082713,0.0005166449,0.0007458717,0.0004097525],"domain_scores_gemma":[0.9944631,0.001239599,0.001202445,0.0007273555,0.002346691,0.00002075826],"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":[0.01893117,0.0007616116,0.1121379,0.2246306,0.001977336,0.000001614313,0.0003445544,0.1395679,0.0001636053,0.1668471,0.001758001,0.3328786],"study_design_scores_gemma":[0.02662878,0.0000115822,0.00007914327,0.003470694,0.001144446,8.446185e-7,0.00003414353,0.9455298,0.00002922656,0.000661657,0.02207037,0.0003393462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4825429,0.1091686,0.3701079,0.004982546,0.001224499,0.02562688,0.00001406193,0.001218951,0.005113679],"genre_scores_gemma":[0.9900787,0.002204539,0.002260481,0.002819445,0.0005488736,0.001724162,0.0002005791,0.00005932765,0.0001039343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8059619,"threshold_uncertainty_score":0.9814231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05504016125027736,"score_gpt":0.321331502369024,"score_spread":0.2662913411187466,"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."}}