{"id":"W2464850106","doi":"10.1007/s11134-016-9488-8","title":"Choosing among heterogeneous server clouds","year":2016,"lang":"en","type":"article","venue":"Queueing Systems","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Server; Blocking (statistics); Computer science; Stationary distribution; Cloud computing; Poisson process; Load balancing (electrical power); Mathematics; Distributed computing; Poisson distribution; Computer network; Statistics; Operating system; Markov chain","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006202382,0.0002434129,0.0003252922,0.0002205942,0.000247225,0.0003241121,0.0003305427,0.00009483298,0.0001327398],"category_scores_gemma":[0.0001650077,0.0001739525,0.0001535872,0.0003900272,0.00007584338,0.001396065,0.000144848,0.0000846735,0.0008949407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001014254,"about_ca_system_score_gemma":0.000008398233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007346194,"about_ca_topic_score_gemma":0.00007920777,"domain_scores_codex":[0.9984108,0.00004357174,0.0004086415,0.0004182858,0.0002888548,0.0004298132],"domain_scores_gemma":[0.9988728,0.00009095077,0.000355031,0.0005263886,0.0001319631,0.00002292157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002172416,0.0002306583,0.4193263,0.001683063,0.000994178,0.0005494465,0.0002955841,0.07251037,0.02130958,0.4605314,0.004374502,0.01797763],"study_design_scores_gemma":[0.009312436,0.0001294802,0.03020451,0.01434137,0.002020727,0.0002390247,0.001954965,0.2906118,0.007923161,0.08015026,0.5531396,0.009972695],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980192,0.0002307763,0.01058286,0.0001731103,0.001139083,0.0002243929,0.000001489534,0.0005847955,0.006871508],"genre_scores_gemma":[0.9948729,0.000003571217,0.00003394896,0.0002494164,0.002048868,0.00002728805,0.000003782809,0.00006662074,0.002693598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5487651,"threshold_uncertainty_score":0.999883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01180901223012604,"score_gpt":0.2141525646057336,"score_spread":0.2023435523756076,"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."}}