{"id":"W2026226766","doi":"10.1007/s11134-008-9064-y","title":"Approximations for the M/GI/N+GI type call center","year":2008,"lang":"en","type":"article","venue":"Queueing Systems","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Queue; Poisson distribution; Laplace transform; Exponential function; Mathematics; Computer science; Server; Workload; Applied mathematics; Mathematical optimization; Mathematical analysis; Statistics; Computer network","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":[0.004639165,0.0009684117,0.001256899,0.00169263,0.00166657,0.003309331,0.005265503,0.002404399,0.01013947],"category_scores_gemma":[0.01860957,0.0007724841,0.001266957,0.002305762,0.00218802,0.003665843,0.002046379,0.003232038,0.002202585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007631084,"about_ca_system_score_gemma":0.003852704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02848431,"about_ca_topic_score_gemma":0.0229815,"domain_scores_codex":[0.9984521,0.0005309941,0.00003604951,0.0001663257,0.0004083588,0.0004061795],"domain_scores_gemma":[0.9938737,0.003553753,0.0003900511,0.0007363493,0.0009366695,0.0005095156],"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":[0.0001844057,0.00008574902,0.001279352,0.00008581185,0.00002744663,0.0001306315,0.0002455042,0.561188,0.0007202082,0.4118702,0.01097739,0.01320536],"study_design_scores_gemma":[0.000007023629,0.000005863136,0.0001446773,0.00001262511,0.000008185542,0.00002069224,0.00002964982,0.9753284,0.0001160923,0.02348329,0.0008336404,0.00000972648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05569103,0.001939938,0.8869693,0.002269363,0.0005487062,0.0001072398,0.0004677078,0.0009405811,0.05106618],"genre_scores_gemma":[0.79792,0.001424557,0.1575941,0.0007768106,0.0006366154,0.0002284744,0.0004858397,0.0007420622,0.04019145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02848431,"threshold_uncertainty_score":0.05663705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03254360343862187,"score_gpt":0.2431694018438913,"score_spread":0.2106257984052694,"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."}}