{"id":"W2170748328","doi":"10.1109/lcomm.2014.011214.132606","title":"Probability Distribution of End-to-End Delay in a Highway VANET","year":2014,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Vehicular ad hoc network; Wireless ad hoc network; Computer science; Computer network; End-to-end principle; Probability distribution; End-to-end delay; Wireless; Telecommunications; Network packet; Mathematics; Statistics","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":[0.001896473,0.000485004,0.000640345,0.001313417,0.0005852347,0.001210437,0.001220485,0.0008973727,0.001858948],"category_scores_gemma":[0.01054633,0.0004276282,0.0003523185,0.001361438,0.00103527,0.001597581,0.0007223179,0.0009504913,0.0004127932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001268532,"about_ca_system_score_gemma":0.0005210564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002756148,"about_ca_topic_score_gemma":0.001711759,"domain_scores_codex":[0.9989393,0.0002262163,0.0000706655,0.0002445734,0.0003292746,0.0001900142],"domain_scores_gemma":[0.9895684,0.007197923,0.001058081,0.0004651588,0.001510489,0.0001999949],"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":[0.0003155385,0.00005460382,0.01244089,0.0001281041,0.00005679756,0.0006000864,0.0002124682,0.9171687,0.004968599,0.051722,0.001782421,0.01054971],"study_design_scores_gemma":[0.00001667195,0.0000744116,0.003095551,0.00002450161,0.00002252779,0.0004160673,0.0001460542,0.9821472,0.002614665,0.01033513,0.001056933,0.00005043331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4254492,0.001507371,0.56016,0.0008796746,0.0001741969,0.0002035416,0.001214643,0.0008406683,0.009570699],"genre_scores_gemma":[0.9847885,0.0006492999,0.01124897,0.00007745691,0.00005465378,0.00008586037,0.0004337261,0.00006232663,0.002599095],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002756148,"threshold_uncertainty_score":0.01002961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0182558982969784,"score_gpt":0.2258865226153494,"score_spread":0.207630624318371,"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."}}