{"id":"W1660138328","doi":"10.1007/978-0-387-35674-7_6","title":"Tariff-Based Pricing and Admission Control for DiffServ Networks","year":2003,"lang":"en","type":"book-chapter","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Tariff; Admission control; Pricing strategies; Quality of service; Architecture; Control (management); Computer science; Computer network; Differentiated services; Business; Operations research; Marketing; Engineering; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002753009,0.0003874246,0.0004772121,0.00009744196,0.0002051305,0.0001723378,0.0004059265,0.0004078153,0.00007786274],"category_scores_gemma":[0.00002038479,0.0003238784,0.0001707178,0.00003392209,0.00004594677,0.0001140039,0.00004770252,0.0002987533,0.000007196773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004007493,"about_ca_system_score_gemma":0.0000944632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002067022,"about_ca_topic_score_gemma":0.00000755084,"domain_scores_codex":[0.9983687,0.00002747904,0.0003644816,0.0006663615,0.0002159459,0.0003570256],"domain_scores_gemma":[0.998448,0.0004703687,0.0002140318,0.0004918944,0.0001257609,0.0002499823],"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":[0.00004614754,0.00001617333,0.00001214554,0.00002692065,0.00005912534,0.00000814161,0.000007746413,0.004917976,0.000002221361,0.6453639,0.01299619,0.3365434],"study_design_scores_gemma":[0.001693465,0.0001310699,0.000008136024,0.0001147945,0.00005597698,0.000005313969,5.225141e-7,0.7477289,0.000001635869,0.00511462,0.2447899,0.0003556407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.000001747578,0.00158217,0.9456241,0.001983616,0.0005699177,0.00080164,0.000003901487,0.0002348042,0.04919811],"genre_scores_gemma":[0.101621,0.0003238194,0.05899617,0.02906011,0.001348509,0.0002352393,0.00005457698,0.0001815445,0.808179],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8866279,"threshold_uncertainty_score":0.9999213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01028722136651046,"score_gpt":0.2010709497649691,"score_spread":0.1907837283984586,"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."}}