{"id":"W2101917791","doi":"10.1007/3-540-45551-5_46","title":"Intelligent Traffic Conditioners for Assured Forwarding Based Differentiated Services Networks","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":83,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Computer science; Bandwidth (computing); Computer network; Enhanced Data Rates for GSM Evolution; Conditioners; Intelligent Network; Service (business); Telecommunications; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006743124,0.000692415,0.0007385965,0.0006959079,0.0004331091,0.0008098487,0.002805847,0.0004667171,0.00006506684],"category_scores_gemma":[0.00001537265,0.0006477825,0.0003166729,0.0005656327,0.0003630562,0.0004370291,0.0002448118,0.0006605627,0.00002166648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000231956,"about_ca_system_score_gemma":0.0003469805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005361439,"about_ca_topic_score_gemma":0.00006569536,"domain_scores_codex":[0.9958861,0.00005442519,0.0007073222,0.001670982,0.0007631298,0.0009180011],"domain_scores_gemma":[0.9972155,0.0008552771,0.0003544144,0.001036841,0.0002803759,0.0002576036],"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":[0.00001569716,0.00001910507,0.000002982769,0.0000219625,0.00002032914,0.000009483555,0.00006640273,0.519168,0.000002747018,0.003248889,0.0000201284,0.4774042],"study_design_scores_gemma":[0.0006973114,0.0001721784,0.00001729197,0.0004572796,0.00003764029,0.00001143422,1.630027e-7,0.981155,0.0000555939,0.01323926,0.003462875,0.0006939408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001123378,0.0005837368,0.9947127,0.0005743423,0.002243794,0.0009434879,0.00001463228,0.0004067726,0.0004082727],"genre_scores_gemma":[0.9234017,0.0000590126,0.07262296,0.00269584,0.0008214741,0.00008104798,0.00009821534,0.00006341509,0.0001563947],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9232893,"threshold_uncertainty_score":0.9995974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01109782146976253,"score_gpt":0.2249901650555645,"score_spread":0.213892343585802,"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."}}