{"id":"W2036875481","doi":"10.1016/j.pmcj.2010.09.002","title":"An efficient routing protocol for connecting vehicular networks to the Internet","year":2010,"lang":"en","type":"article","venue":"Pervasive and Mobile Computing","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; University of Waterloo","funders":"","keywords":"Computer science; Computer network; Network packet; Routing protocol; Flooding (psychology); Overhead (engineering); Vehicular ad hoc network; The Internet; Protocol (science); Scheme (mathematics); Internet Protocol; Wireless ad hoc network; Distributed computing; Wireless; Telecommunications; World Wide Web","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":[],"consensus_categories":[],"category_scores_codex":[0.0007327352,0.0002395959,0.0002251871,0.00004310479,0.0003256571,0.00020572,0.0002900616,0.0001103713,0.00001171886],"category_scores_gemma":[0.00008002213,0.0001917053,0.00008183706,0.0001434843,0.00002871805,0.00005526166,0.0001408257,0.0004643925,0.000005384384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002961548,"about_ca_system_score_gemma":0.00001165721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002066371,"about_ca_topic_score_gemma":0.00007778259,"domain_scores_codex":[0.9986165,0.00004299851,0.0003011953,0.0003622333,0.0001192839,0.0005577603],"domain_scores_gemma":[0.9990574,0.0002739938,0.00006202635,0.000330753,0.0001010605,0.0001748311],"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":[0.000008790818,0.00001790505,0.000350598,0.00004402496,0.00002457348,0.000003389149,0.001433177,0.9634146,0.001493062,0.0001228048,0.0002624093,0.03282463],"study_design_scores_gemma":[0.0004332251,0.0001220202,0.0003473944,0.0001039125,0.00001463738,0.00003878722,0.00033784,0.9734318,0.0009335935,0.000005635721,0.02398378,0.0002474313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6785375,0.000029482,0.2788413,0.00002858769,0.000398036,0.04180732,0.000002047098,0.0002696782,0.0000860529],"genre_scores_gemma":[0.966195,4.081983e-7,0.003674697,0.0001623582,0.001033555,0.02885284,0.000008912479,0.00006641562,0.000005837487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2876574,"threshold_uncertainty_score":0.7817514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009233094026874025,"score_gpt":0.2641155682407446,"score_spread":0.2548824742138706,"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."}}