{"id":"W2079437050","doi":"10.1504/ijaacs.2014.058016","title":"On improving delay performance of IEEE 802.11p vehicular safety communication","year":2013,"lang":"en","type":"article","venue":"International Journal of Autonomous and Adaptive Communications Systems","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; University of Carthage","keywords":"Computer science; IEEE 802.11p; Computer network; Dedicated short-range communications; Network packet; Wireless; Vehicular ad hoc network; Wireless ad hoc network; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001197236,0.0008648958,0.0002970069,0.0006386823,0.0004255962,0.0009374522,0.0009968498,0.000399294,0.0008481179],"category_scores_gemma":[0.002384195,0.0001946284,0.0001825126,0.0004111704,0.000351552,0.001058179,0.0005937022,0.0005423299,0.0004642124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005552097,"about_ca_system_score_gemma":0.0008687219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001262931,"about_ca_topic_score_gemma":0.001381688,"domain_scores_codex":[0.9991783,0.0002193818,0.00006688981,0.0001585807,0.000264159,0.0001124997],"domain_scores_gemma":[0.9989432,0.0003614321,0.000101727,0.0001071515,0.0004495481,0.00003708429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004111624,0.0002740302,0.004549647,0.0005310475,0.0001008255,0.0002916711,0.0002991554,0.2545668,0.1622001,0.03236428,0.003159379,0.541252],"study_design_scores_gemma":[0.00004578245,0.0008254409,0.0009716497,0.00004220075,0.00008447659,0.0004453423,0.0001036586,0.8932384,0.07910768,0.004319043,0.02076874,0.00004766686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06624771,0.003878899,0.9208064,0.0002129401,0.0002815714,0.00008637882,0.00003196535,0.0007562764,0.007697859],"genre_scores_gemma":[0.8701285,0.002185322,0.1234887,0.0001352061,0.0001467334,0.00006169698,0.0001020845,0.00005618967,0.003695539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001262931,"threshold_uncertainty_score":0.006331682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0110332000589079,"score_gpt":0.2148528255585845,"score_spread":0.2038196254996766,"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."}}