{"id":"W1890330007","doi":"10.1109/cdc.1996.573565","title":"A framework for dimensioning and connection acceptance control in ATM networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Dimensioning; Variable bitrate; Computer science; Constant bitrate; Quality of service; Asynchronous Transfer Mode; Computer network; Moment (physics); Connection (principal bundle); Constant (computer programming); Leaky bucket; Admission control; Real-time computing; Mathematics; Engineering","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":[0.003261983,0.0009655972,0.00104686,0.0005797073,0.001076905,0.002421974,0.003090268,0.001431478,0.003261753],"category_scores_gemma":[0.005152398,0.0005392388,0.0009888673,0.0008928347,0.003078954,0.002950567,0.001408455,0.002945769,0.0004402232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002102714,"about_ca_system_score_gemma":0.001755524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003464042,"about_ca_topic_score_gemma":0.002120058,"domain_scores_codex":[0.9985207,0.0005210432,0.00006912203,0.0003066516,0.000439318,0.00014312],"domain_scores_gemma":[0.9977512,0.001235378,0.0002320234,0.0002261227,0.0003706526,0.0001846943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002126434,0.00003430631,0.000125672,0.00004124846,0.00001404314,0.00005959392,0.0001487773,0.1769285,0.00144596,0.8084734,0.0007827093,0.01192454],"study_design_scores_gemma":[0.00001739648,0.00004791555,0.00005582281,0.0000189656,0.00001216425,0.00002243064,0.00002493243,0.6980308,0.0004203959,0.295813,0.005518971,0.00001718705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003579895,0.0003353691,0.9924921,0.0002793591,0.00008201927,0.00003332685,0.00003256129,0.00008728774,0.003078067],"genre_scores_gemma":[0.6038821,0.001330586,0.3840329,0.000417635,0.0006474524,0.0005999262,0.0001173401,0.0001175661,0.008854331],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003464042,"threshold_uncertainty_score":0.01725119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01556279902581716,"score_gpt":0.2366944508292875,"score_spread":0.2211316518034704,"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."}}