{"id":"W2045099094","doi":"10.1016/j.adhoc.2010.06.006","title":"Mobility impact in IEEE 802.11p infrastructureless vehicular networks","year":2010,"lang":"en","type":"article","venue":"Ad Hoc Networks","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":181,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer network; Computer science; IEEE 802.11p; Unicast; Vehicular ad hoc network; Wireless ad hoc network; IEEE 802.11; Network packet; Node (physics); Throughput; Mobile ad hoc network; Network performance; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0008662876,0.0008291017,0.0008655759,0.0002069739,0.000144712,0.0001777319,0.00081246,0.00114711,0.0003630631],"category_scores_gemma":[0.00004161043,0.0008098141,0.0003888709,0.001112529,0.0001979465,0.0004158157,0.0001350831,0.003737122,0.00005544498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002962156,"about_ca_system_score_gemma":0.00006772789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005146228,"about_ca_topic_score_gemma":0.001820753,"domain_scores_codex":[0.9959341,0.0001431383,0.0008566643,0.0007805342,0.0004282412,0.001857279],"domain_scores_gemma":[0.9975248,0.0002438486,0.0001273891,0.001449888,0.00009872454,0.0005553379],"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":[0.00004530755,0.00005351132,0.008340186,0.00002538603,0.000103703,0.0001074452,0.00007622852,0.9553475,0.0005020351,0.00004910744,0.004089387,0.03126023],"study_design_scores_gemma":[0.0008669115,0.00006516625,0.05427986,0.00006911025,0.000041469,0.00007516304,0.00001409557,0.937195,0.00008344268,0.0002875186,0.006215678,0.0008066037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9586288,0.00625017,0.02884107,0.00002933915,0.003881312,0.0007894355,0.00001244724,0.0008043758,0.0007630876],"genre_scores_gemma":[0.9958984,0.001063514,0.0008827982,0.0001444688,0.001533236,0.0001090928,0.0001066738,0.0002245742,0.00003719373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04593968,"threshold_uncertainty_score":0.9994352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003899155917060626,"score_gpt":0.2148461051444427,"score_spread":0.2109469492273821,"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."}}