{"id":"W2984221606","doi":"10.1109/jproc.2019.2948302","title":"5G Vehicle-to-Everything Services: Gearing Up for Security and Privacy","year":2019,"lang":"en","type":"article","venue":"Proceedings of the IEEE","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":147,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of New Brunswick","funders":"","keywords":"Computer security; Computer science; Internet privacy; Security analysis; Reliability (semiconductor); Security service; Service (business); Business; Information security","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":[0.001747145,0.001161464,0.0006873698,0.001565395,0.002025263,0.004693879,0.001746866,0.003587851,0.004986815],"category_scores_gemma":[0.003390375,0.0005016575,0.0007948171,0.001966786,0.001804726,0.009617066,0.005447404,0.004514636,0.002137775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002060999,"about_ca_system_score_gemma":0.001892592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005305266,"about_ca_topic_score_gemma":0.003643731,"domain_scores_codex":[0.9979597,0.0004671424,0.0001021973,0.0002151754,0.0007727481,0.000482919],"domain_scores_gemma":[0.9981626,0.0004215667,0.0001677223,0.0004137947,0.0006252673,0.0002089713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001920232,0.0000897236,0.003338822,0.001049229,0.00009640066,0.0008170124,0.001026642,0.008380333,0.009375718,0.5567948,0.06158234,0.3572569],"study_design_scores_gemma":[0.0000238137,0.0002811212,0.001739863,0.0008223263,0.0001078085,0.002139958,0.001197891,0.0511231,0.00832851,0.1617502,0.772368,0.0001174692],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03606163,0.07412507,0.6590705,0.04721371,0.00627545,0.000658928,0.0009111149,0.003482743,0.1722009],"genre_scores_gemma":[0.7542037,0.07195726,0.1149554,0.01151886,0.004185692,0.0004096174,0.001747295,0.0004454393,0.04057674],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005305266,"threshold_uncertainty_score":0.01668257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004890842389355934,"score_gpt":0.1901672968000984,"score_spread":0.1852764544107424,"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."}}