{"id":"W2088072318","doi":"10.1109/glocomw.2007.4437821","title":"Location-Based Message Aggregation in Vehicular Ad Hoc Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer network; Computer science; Overhead (engineering); Scalability; Node (physics); Wireless ad hoc network; Vehicular ad hoc network; Cluster analysis; Routing protocol; Distributed computing; Locality; Protocol (science); Routing (electronic design automation); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001374259,0.0003926052,0.0007904217,0.0009399393,0.0008730661,0.001143597,0.001048681,0.0008222265,0.0004526516],"category_scores_gemma":[0.002381043,0.0003287478,0.0003526783,0.001416021,0.00070338,0.001662259,0.001057739,0.0005275473,0.0003045721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000634049,"about_ca_system_score_gemma":0.0004912796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001894173,"about_ca_topic_score_gemma":0.001307064,"domain_scores_codex":[0.9987919,0.0004462434,0.0001064693,0.000133624,0.0004470873,0.00007473309],"domain_scores_gemma":[0.9990515,0.0004290908,0.0001268848,0.0001755458,0.0001794352,0.00003754236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003387249,0.000140068,0.002168809,0.0004829618,0.0001331622,0.0009895547,0.001151327,0.3558257,0.03714291,0.2235587,0.00858084,0.3694873],"study_design_scores_gemma":[0.00004467255,0.0001851921,0.0005847014,0.00003891485,0.00007270535,0.0004040013,0.0001244314,0.9094813,0.0124966,0.04981071,0.02670949,0.00004729408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01516909,0.002743369,0.9775158,0.0002834554,0.0001629431,0.00009945107,0.00003106821,0.00110316,0.002891751],"genre_scores_gemma":[0.6832075,0.003043145,0.3071871,0.0001793629,0.0003339754,0.000269386,0.0002230928,0.00009792748,0.005458593],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001894173,"threshold_uncertainty_score":0.007267892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008141125627559379,"score_gpt":0.2292827346751125,"score_spread":0.2211416090475531,"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."}}