{"id":"W2741500941","doi":"","title":"Modeling Daily Arrivals to a Telephone Call Center","year":2003,"lang":"fr","type":"article","venue":"Les Cahiers du GERAD","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Focus (optics); Center (category theory); Goodness of fit; Call management; Variance (accounting); Statistics; Mathematics; Telecommunications; Call control","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":[0.002280344,0.0008278409,0.0007794786,0.0009771911,0.0006158063,0.001928278,0.002277791,0.002329354,0.002244641],"category_scores_gemma":[0.01136951,0.000758921,0.0006930009,0.001600463,0.00074412,0.002017925,0.0008892844,0.001983495,0.0004898132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002050664,"about_ca_system_score_gemma":0.001372545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02364952,"about_ca_topic_score_gemma":0.01613031,"domain_scores_codex":[0.9986498,0.0005481202,0.0000624176,0.0002448154,0.0002573031,0.0002376342],"domain_scores_gemma":[0.9944928,0.003272188,0.001027361,0.0003203029,0.0006195375,0.0002678146],"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":[0.00004497871,0.00006577946,0.004159287,0.00001832856,0.00002701265,0.00006734444,0.000161169,0.9768983,0.0005263117,0.01408238,0.0005160433,0.00343305],"study_design_scores_gemma":[0.000006185771,0.00001432192,0.0005033918,0.000001995323,0.000004125024,0.00001088934,0.00002243277,0.9969364,0.00006299446,0.002237864,0.0001918768,0.000007560355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5824428,0.0003412137,0.4101493,0.001081311,0.00009553221,0.0001352937,0.0008299737,0.0005229551,0.00440161],"genre_scores_gemma":[0.9738631,0.0003039651,0.02207798,0.00008601821,0.00008383964,0.0001267768,0.0004955887,0.000052213,0.002910638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02364952,"threshold_uncertainty_score":0.04702371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01035860234003744,"score_gpt":0.2144726329398225,"score_spread":0.2041140305997851,"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."}}