{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000289915,0.0002166056,0.0002131869,0.0002836805,0.0001467879,0.000123194,0.0004677597,0.00008155655,0.00001140588],"category_scores_gemma":[0.00002176437,0.0002479846,0.00004936196,0.0005645774,0.00001401387,0.0005083748,0.0001571601,0.0001613365,0.0000333194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001152612,"about_ca_system_score_gemma":0.00002899602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003761031,"about_ca_topic_score_gemma":0.00002746064,"domain_scores_codex":[0.9983023,0.00006825549,0.0004065759,0.0004908468,0.000327858,0.0004041075],"domain_scores_gemma":[0.9990098,0.0002351117,0.00008713634,0.0004155216,0.0001248483,0.0001275163],"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":[0.00001242658,0.00002853869,0.00191964,0.00001744671,0.00001065244,0.0000179437,0.0003214574,0.9392704,0.00002992705,0.001388088,1.965331e-7,0.05698325],"study_design_scores_gemma":[0.0007211943,0.00001557236,0.04353399,0.0001351886,0.000008789754,0.000001951305,0.00001008796,0.9552063,0.000005659412,0.00001563461,0.00009204853,0.0002535419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4163625,0.00003450123,0.5828953,0.00003314291,0.0001685043,0.0002929692,2.243688e-7,0.0001745203,0.00003833959],"genre_scores_gemma":[0.9496077,0.000008631901,0.05012239,0.0001209037,0.00007720531,0.00001921742,0.000001723372,0.00001617505,0.00002607662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5332452,"threshold_uncertainty_score":0.9999973,"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."}}