{"id":"W2152426285","doi":"10.1109/lcn.2009.5355052","title":"Vehicle traffic congestion management in vehicular ad-hoc networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; University of Ottawa","funders":"","keywords":"Vehicular ad hoc network; Computer science; Network congestion; Computer network; Controller (irrigation); Wireless ad hoc network; Traffic congestion; Network traffic control; Traffic congestion reconstruction with Kerner's three-phase theory; Engineering; Network packet; Telecommunications; Transport engineering; Wireless","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":[0.0002137191,0.0002220217,0.0002107425,0.0001242885,0.00003485065,0.00004853476,0.0001764853,0.0001518312,0.00008632168],"category_scores_gemma":[0.000002690343,0.000233327,0.0000688761,0.0003966561,0.00001629988,0.0001464669,0.00001968469,0.0002949656,0.0001034083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001470788,"about_ca_system_score_gemma":0.000003839987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000104495,"about_ca_topic_score_gemma":0.00005644254,"domain_scores_codex":[0.9986932,0.00003356916,0.0002884457,0.0002588804,0.0001914545,0.0005344512],"domain_scores_gemma":[0.9995203,0.00001950505,0.00001865522,0.0003129984,0.00001521193,0.0001133331],"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":[0.000008787756,0.00003162462,0.00002541541,0.00001016308,0.00002372232,0.0001076906,0.00002749362,0.8419336,0.00005406347,0.0003675822,0.001901398,0.1555085],"study_design_scores_gemma":[0.0006778036,0.0000496299,0.01551518,0.00004919045,0.00001916212,0.0000086148,0.00002916932,0.9712809,0.00003077903,0.00008695976,0.01197337,0.0002792822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693941,0.007399247,0.007482931,0.0003396683,0.0004025367,0.0006125438,6.723445e-7,0.001236426,0.01313186],"genre_scores_gemma":[0.9964999,0.00140535,0.001374818,0.0002708366,0.0000887141,0.00002182831,0.00001909734,0.00003661603,0.0002828636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1552292,"threshold_uncertainty_score":0.9514798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005197847983532128,"score_gpt":0.1949530639109661,"score_spread":0.189755215927434,"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."}}