{"id":"W2507483638","doi":"10.1002/sec.1586","title":"Towards a secure hybrid adaptive gateway discovery mechanism for intelligent transportation systems","year":2016,"lang":"en","type":"article","venue":"Security and Communication Networks","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada","keywords":"Computer science; Scalability; Computer network; Default gateway; Gateway (web page); Intelligent transportation system; Protocol (science); Computer security; Smart city; Authentication (law); Internet of Things; World Wide Web; Operating system","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":[0.0003041535,0.0002146557,0.0002450761,0.00004497326,0.0001506022,0.00009030577,0.0002835861,0.0001514047,0.000006902684],"category_scores_gemma":[0.000009526396,0.0001781893,0.00008919014,0.00009776444,0.00006499417,0.0003273406,0.00003013804,0.0002210849,0.000003070288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000865612,"about_ca_system_score_gemma":0.00001644339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003479105,"about_ca_topic_score_gemma":0.0003108985,"domain_scores_codex":[0.9989097,0.00009628828,0.0003383062,0.0002131231,0.0001322808,0.0003102605],"domain_scores_gemma":[0.9990374,0.000167492,0.00008128559,0.0005140835,0.00009754977,0.0001022297],"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":[0.0001380923,0.00007008066,0.00005015279,0.0001484534,0.0002792828,0.000003710004,0.001997732,0.4937344,0.0001673115,0.4814076,0.002231211,0.01977195],"study_design_scores_gemma":[0.0005677341,0.00008014534,0.00007130035,0.000389101,0.00006653303,0.000009770349,0.0003680308,0.9660733,0.00055948,0.02550216,0.005954782,0.0003577101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07398301,0.007893361,0.9156471,0.0003144979,0.0003980511,0.0008976902,0.000115752,0.000315494,0.0004349793],"genre_scores_gemma":[0.9907255,0.008033414,0.0005165653,0.00005350358,0.0001330677,0.0002553047,0.0001816094,0.00004454498,0.00005650997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9167425,"threshold_uncertainty_score":0.7266349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009618631915648596,"score_gpt":0.2030525240482758,"score_spread":0.1934338921326272,"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."}}