{"id":"W2805800502","doi":"10.1109/jiot.2018.2844826","title":"DBCC: Leveraging Link Perception for Distributed Beacon Congestion Control in VANETs","year":2018,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Beacon; Computer network; Non-line-of-sight propagation; Real-time computing; Polling; Network packet; Wireless; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007325331,0.0001968337,0.0003187752,0.0001776949,0.0000446573,0.00009185675,0.0002527275,0.0001711925,0.00008073644],"category_scores_gemma":[0.00008185982,0.0001999656,0.0001355221,0.00009469744,0.00006426506,0.0004332494,0.00001462477,0.0005566727,0.00001799141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002962541,"about_ca_system_score_gemma":0.00002155807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003999091,"about_ca_topic_score_gemma":0.00002606341,"domain_scores_codex":[0.9985963,0.00005564193,0.0005705064,0.000166094,0.0002179989,0.0003934533],"domain_scores_gemma":[0.9992699,0.0000994537,0.0001794599,0.0001302631,0.0002087547,0.0001121516],"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":[0.0004040507,0.00006577098,0.002578879,0.0001462186,0.0002957474,0.0000510417,0.004179105,0.8216051,0.1087089,0.00005011971,0.01729852,0.04461647],"study_design_scores_gemma":[0.001914173,0.0002266981,0.003652185,0.000500823,0.00004724467,0.0002594651,0.00006334869,0.9854794,0.004296361,0.0004323713,0.002911278,0.0002166536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6019091,0.0001244035,0.3958851,0.000204593,0.001509203,0.00018902,0.000009097726,0.00006998177,0.0000995552],"genre_scores_gemma":[0.996618,0.00003368597,0.002027158,0.0001515995,0.001041937,0.000009474926,0.00002060559,0.00004341644,0.00005409572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3947089,"threshold_uncertainty_score":0.8154358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.010738929305801,"score_gpt":0.2304262242112438,"score_spread":0.2196872949054428,"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."}}