{"id":"W2095784707","doi":"10.1007/s11134-006-7419-9","title":"Multi-layered round robin routing for parallel servers","year":2006,"lang":"en","type":"article","venue":"Queueing Systems","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Equal-cost multi-path routing; Distributed computing; Static routing; Scheduling (production processes); Computer network; Queue; Routing (electronic design automation); Mathematical optimization; Mathematics; Routing protocol","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0039715,0.0008328565,0.001301179,0.0009365558,0.001757585,0.002754512,0.002743778,0.0009559318,0.003849243],"category_scores_gemma":[0.01046286,0.0009446163,0.0009716584,0.001039333,0.0009416456,0.002739616,0.00172606,0.001576207,0.001101879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002425163,"about_ca_system_score_gemma":0.002611681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0058965,"about_ca_topic_score_gemma":0.007415568,"domain_scores_codex":[0.9976516,0.0009249935,0.0001601847,0.0002660749,0.0005327964,0.0004643589],"domain_scores_gemma":[0.9959518,0.001620065,0.0003066848,0.001057752,0.0007278561,0.0003357681],"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":[0.001000771,0.0002311605,0.001014888,0.000165885,0.0001133499,0.0002811452,0.0003046222,0.7674839,0.01824332,0.1005712,0.00598628,0.1046034],"study_design_scores_gemma":[0.00001403845,0.00002932513,0.00007856663,0.000005641491,0.00001727737,0.0000311015,0.00001718625,0.9819435,0.001958426,0.01519449,0.0006924897,0.00001784281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0286528,0.0002594855,0.9672005,0.0002194581,0.0001009163,0.00008326447,0.00009091431,0.001160309,0.002232278],"genre_scores_gemma":[0.5906165,0.0003397129,0.4020702,0.0001480562,0.0001133853,0.0001411513,0.0002245358,0.0003675,0.005979036],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0058965,"threshold_uncertainty_score":0.02100354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02332507120211842,"score_gpt":0.2441921547155638,"score_spread":0.2208670835134454,"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."}}