{"id":"W2078438985","doi":"10.5555/1400549.1400661","title":"Using simulation to evaluate traffic engineering management services in maritime networks","year":2008,"lang":"en","type":"article","venue":"Spring Simulation Multiconference","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Communications Research Centre Canada","funders":"","keywords":"Network traffic simulation; Computer science; Traffic generation model; Computer network; Quality of service; Traffic engineering; Multiprotocol Label Switching; Network traffic control; Traffic shaping; Internet traffic engineering; Queueing theory; Traffic optimization; Floating car data; Engineering; Transport engineering; Traffic congestion","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":[0.001749775,0.0008500038,0.0005398109,0.0009124785,0.0004097018,0.0008626599,0.0006621318,0.000813591,0.0008497086],"category_scores_gemma":[0.006178758,0.00026369,0.0003667313,0.0007805601,0.0005345963,0.0008394879,0.0004741164,0.0006319977,0.0001011934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001777562,"about_ca_system_score_gemma":0.0008311044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01209505,"about_ca_topic_score_gemma":0.006572812,"domain_scores_codex":[0.9988954,0.0006855149,0.00004903667,0.00006047925,0.000196526,0.0001129979],"domain_scores_gemma":[0.9946039,0.004232768,0.0002571248,0.0002750089,0.0005053151,0.0001258344],"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":[0.0001394521,0.0001445836,0.003636634,0.00002671657,0.00003136599,0.00003162307,0.00005455848,0.9886222,0.001349028,0.001589811,0.0001261509,0.004247847],"study_design_scores_gemma":[0.00001343308,0.00009795936,0.0003682307,0.000004594235,0.000009087177,0.000005963496,0.00002663941,0.9973507,0.001570735,0.0003643306,0.0001830944,0.000005250925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.965691,0.0001635427,0.02748545,0.0001412406,0.00004702919,0.0001258119,0.0002687163,0.0003065209,0.005770727],"genre_scores_gemma":[0.9896632,0.0001229694,0.009406789,0.0000216754,0.000004960737,0.00009690321,0.0001809865,0.00001886743,0.0004836908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01209505,"threshold_uncertainty_score":0.02404934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03528268473231966,"score_gpt":0.2788323147481344,"score_spread":0.2435496300158147,"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."}}