{"id":"W2150728192","doi":"10.1109/infocom.2008.4544625","title":"Control-plane congestion and provisioning guidelines for OBS networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Header; Offset (computer science); Computer science; Computer network; Network congestion; Forwarding plane; Queueing theory; Bottleneck; Provisioning; Throughput; Routing control plane; Real-time computing; Telecommunications; Network packet; Wireless; Embedded 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005350894,0.00009970521,0.0001375846,0.0000251603,0.00006770936,0.000009379918,0.00005200445,0.0000981321,0.000004859543],"category_scores_gemma":[0.0002448421,0.00008250836,0.00001658332,0.00005484923,0.00005954493,0.00008355973,0.00001482487,0.00008517209,0.000001994825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001205318,"about_ca_system_score_gemma":0.000002448464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001352403,"about_ca_topic_score_gemma":0.000003664052,"domain_scores_codex":[0.9994776,0.000002482976,0.0001674389,0.0001142356,0.00004475068,0.0001935455],"domain_scores_gemma":[0.9995924,0.000184701,0.00001313849,0.00009721058,0.00007890665,0.0000335916],"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":[0.00001948385,0.000003801557,0.0006183938,0.00001744258,0.00001982176,0.000005155333,0.000005343473,0.9319008,0.0003617874,0.005978608,0.01077645,0.05029289],"study_design_scores_gemma":[0.0004969887,0.00005270773,0.0005341112,0.00001904579,0.000007502263,0.00002458765,0.00001274444,0.9904971,0.000112767,0.0008745075,0.007233807,0.0001341409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02798834,0.001590526,0.967829,0.0003862762,0.0001434516,0.0002907738,0.000002422922,0.001323164,0.0004460344],"genre_scores_gemma":[0.7635921,0.0005652122,0.2354247,0.0001213791,0.000118419,0.00004326454,0.000006616461,0.00002019022,0.0001081077],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7356038,"threshold_uncertainty_score":0.3364593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03182258545135074,"score_gpt":0.2608695696500479,"score_spread":0.2290469841986972,"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."}}