{"id":"W2050764267","doi":"10.1002/wcm.939","title":"Analysis of broadcasting delays in vehicular <i>ad hoc</i> networks","year":2010,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Minnesota Department of Transportation","keywords":"Computer science; Broadcasting (networking); Computer network; Correctness; Wireless ad hoc network; Vehicular ad hoc network; Markov chain; Collision; Node (physics); Mobile ad hoc network; Reliability (semiconductor); Markov process; Telecommunications; Wireless; Computer security; Algorithm","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":[0.001021172,0.0003349143,0.0002358955,0.0008202501,0.0003522787,0.0005379054,0.00054397,0.0002987709,0.0004251546],"category_scores_gemma":[0.004311518,0.0002635409,0.0002372701,0.0005407685,0.0006107111,0.0005911717,0.0003636958,0.0002882597,0.00006048373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001520732,"about_ca_system_score_gemma":0.0007602199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004964737,"about_ca_topic_score_gemma":0.002519511,"domain_scores_codex":[0.9996226,0.00009422842,0.00001686105,0.00005503066,0.0001298046,0.00008153904],"domain_scores_gemma":[0.997129,0.001937177,0.0004192546,0.00008816161,0.0003326518,0.00009376167],"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":[0.00005492063,0.00001778345,0.003473485,0.00003084628,0.00002473584,0.00007795856,0.00004688766,0.9716992,0.002880392,0.01598904,0.0002048317,0.005499902],"study_design_scores_gemma":[0.000003833799,0.00003559741,0.000795393,0.000003720491,0.00001005309,0.00004743228,0.00003431011,0.9924477,0.001100358,0.005190219,0.000325665,0.000005646488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6136817,0.0007691359,0.3809605,0.0002014199,0.000033629,0.00005428638,0.000109142,0.0001314848,0.004058699],"genre_scores_gemma":[0.993907,0.0001992094,0.005418201,0.000008965608,0.00000886572,0.00001510616,0.00004222762,0.000008019768,0.0003923626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004964737,"threshold_uncertainty_score":0.01103377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007431768622354802,"score_gpt":0.2290955874626166,"score_spread":0.2216638188402618,"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."}}