{"id":"W3094343460","doi":"10.1109/iscc50000.2020.9219562","title":"Speed Based Distributed Congestion Control Scheme for Vehicular Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Network congestion; Computer network; Packet loss; Vehicular ad hoc network; Transmission (telecommunications); The Internet; Network packet; Intelligent transportation system; Channel (broadcasting); Wireless ad hoc network; Wireless sensor network; Transmission delay; Data transmission; Scheme (mathematics); Real-time computing; Wireless; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008339107,0.0006451006,0.0006576063,0.0008672477,0.0009077477,0.0006756857,0.00157312,0.0003855467,0.001110666],"category_scores_gemma":[0.001911506,0.0001957518,0.0003612047,0.0005004148,0.0005205584,0.0009363489,0.0007326883,0.0006271313,0.0001643203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001143986,"about_ca_system_score_gemma":0.0009869232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004569924,"about_ca_topic_score_gemma":0.00516493,"domain_scores_codex":[0.9994475,0.0001207787,0.00004459931,0.0001186522,0.0001916177,0.00007691099],"domain_scores_gemma":[0.999118,0.0002388663,0.0001056892,0.0000855762,0.0003928412,0.00005907672],"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":[0.0004823084,0.0003335802,0.001387565,0.0002117924,0.0001435306,0.0002353457,0.0003332183,0.6855375,0.04078123,0.04161186,0.00649141,0.2224507],"study_design_scores_gemma":[0.00004483489,0.0001663788,0.0002620278,0.000004941869,0.00002759438,0.00006400144,0.00002179247,0.9901391,0.003671023,0.002804203,0.002766644,0.00002757181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05336216,0.0006830847,0.9400783,0.0002846687,0.0003454156,0.0002986639,0.00006608789,0.0009977286,0.0038839],"genre_scores_gemma":[0.9576591,0.0002091534,0.03941499,0.00005621127,0.00005673248,0.0001318133,0.00008549692,0.00002993455,0.002356659],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004569924,"threshold_uncertainty_score":0.009086609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0111439303512683,"score_gpt":0.1955672151628526,"score_spread":0.1844232848115843,"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."}}