{"id":"W2945644527","doi":"10.1109/tvt.2019.2916936","title":"On the End-to-End Delay in a One-Way VANET","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"End-to-end principle; Vehicular ad hoc network; End-to-end delay; Wireless ad hoc network; Computer network; Computer science; Probability distribution; Range (aeronautics); Wireless; Telecommunications; Engineering; Mathematics; Statistics; Network packet","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":[0.002428541,0.001400628,0.001283102,0.002381878,0.0009968745,0.002257261,0.001751262,0.001187689,0.001842144],"category_scores_gemma":[0.01441703,0.0007820011,0.0007672558,0.002674208,0.002139894,0.004684694,0.001251636,0.001860763,0.0004626367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003345415,"about_ca_system_score_gemma":0.001300028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007402041,"about_ca_topic_score_gemma":0.004107479,"domain_scores_codex":[0.9982374,0.0004532675,0.0001027797,0.0004219696,0.000525753,0.0002588716],"domain_scores_gemma":[0.9880883,0.00953264,0.0008319759,0.0002442921,0.001132859,0.0001699121],"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":[0.00007778933,0.00002518434,0.00095989,0.0001864139,0.0000417533,0.000189681,0.0001436928,0.912801,0.001793955,0.07094623,0.00077624,0.0120582],"study_design_scores_gemma":[0.000005195229,0.00006337227,0.0003389358,0.00006173687,0.00003594249,0.0002173368,0.00009261653,0.9747772,0.0008648037,0.0217158,0.001792911,0.00003418371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04487167,0.008568806,0.9331223,0.001264718,0.0003787284,0.0000873008,0.0001868596,0.0002218737,0.01129778],"genre_scores_gemma":[0.9371101,0.01661553,0.03769179,0.0004895307,0.0004586386,0.0001623317,0.0001608898,0.0002383172,0.00707271],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007402041,"threshold_uncertainty_score":0.0242728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007975429753616864,"score_gpt":0.1955129421061687,"score_spread":0.1875375123525518,"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."}}