{"id":"W3080531147","doi":"10.1016/j.comnet.2020.107440","title":"Delivering Video-on-Demand services with IEEE 802.11p to major non-urban roads: A stochastic performance analysis","year":2020,"lang":"en","type":"article","venue":"Computer Networks","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University; University of Ottawa","funders":"","keywords":"Computer science; Probabilistic logic; Service (business); Codec; Throughput; Blocking (statistics); IEEE 802; Discrete event simulation; Computer network; Real-time computing; Simulation; Quality of service; Telecommunications; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003903107,0.001403073,0.00107736,0.001242474,0.0008827102,0.001725233,0.001661413,0.001437343,0.001711799],"category_scores_gemma":[0.01028539,0.000847106,0.0006758103,0.001554046,0.001588217,0.001920229,0.001385914,0.001060158,0.0002233989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004998614,"about_ca_system_score_gemma":0.002155346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03092788,"about_ca_topic_score_gemma":0.02059854,"domain_scores_codex":[0.9980392,0.0006064793,0.00005844317,0.0002411624,0.0004729766,0.0005818793],"domain_scores_gemma":[0.9912713,0.006404249,0.0007252325,0.0001805897,0.001174799,0.0002438749],"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":[0.00009399329,0.00005498729,0.001466994,0.00005570315,0.00003214711,0.0001022452,0.00003946025,0.9800284,0.001396421,0.01099353,0.001040253,0.004695805],"study_design_scores_gemma":[0.000004163572,0.00003438503,0.0004190864,0.000003908464,0.00001242817,0.0000271631,0.00002344681,0.9976624,0.0002907759,0.001432837,0.00008230458,0.00000711077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4551096,0.002553585,0.5213048,0.002549688,0.0001370859,0.0002981204,0.0008901343,0.0005736559,0.01658329],"genre_scores_gemma":[0.9896408,0.000731622,0.007208535,0.00008500584,0.00006123314,0.00004480985,0.0001724028,0.0000522847,0.002003375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03092788,"threshold_uncertainty_score":0.06149572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004442533530198014,"score_gpt":0.1673648177274307,"score_spread":0.1629222841972326,"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."}}