{"id":"W2071777054","doi":"10.1016/j.peva.2011.11.001","title":"Analysis of discrete-time MAP/G/1 queue under workload control","year":2011,"lang":"en","type":"article","venue":"Performance Evaluation","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Ministry of Education, Science and Technology; National Research Foundation of Korea","keywords":"Workload; Queue; Computer science; Idle; Service (business); Real-time computing; Queueing theory; Computer network; Operating system","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":[0.001738662,0.0005635786,0.0007824852,0.0008191254,0.0005921284,0.001592213,0.001270495,0.0005105656,0.001950323],"category_scores_gemma":[0.00582017,0.0002306699,0.0004410346,0.0006678028,0.0008101437,0.001198601,0.0006073062,0.0007007218,0.0001194864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002326162,"about_ca_system_score_gemma":0.00200067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01359387,"about_ca_topic_score_gemma":0.004164617,"domain_scores_codex":[0.9990469,0.0002066311,0.0000225113,0.0001203921,0.0003687009,0.0002348601],"domain_scores_gemma":[0.9979092,0.001075288,0.000199324,0.00008741793,0.0005848086,0.0001438807],"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":[0.0002494431,0.00009904631,0.002866637,0.0001406374,0.00005130865,0.0002289983,0.000146748,0.8823724,0.009082593,0.08924729,0.001676372,0.01383854],"study_design_scores_gemma":[0.000001466607,0.000006357346,0.000154561,9.523027e-7,0.000002939415,0.000005774712,0.000006197819,0.9982858,0.0001666456,0.001330048,0.00003746246,0.000001807981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3157379,0.001207754,0.6720107,0.0009706589,0.0002222241,0.0001070416,0.0001735752,0.0004405108,0.009129725],"genre_scores_gemma":[0.9908431,0.0001828924,0.006825988,0.00004686552,0.00006261373,0.00001844597,0.00004237829,0.00002894946,0.001948947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01359387,"threshold_uncertainty_score":0.02702945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02871462247219972,"score_gpt":0.2628722531438041,"score_spread":0.2341576306716044,"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."}}