{"id":"W2904405145","doi":"10.1109/antem.2018.8572847","title":"Cyber Security Challenges in Autonomous Vehicle: Their Impact on RF Sensor and Wireless Technologies","year":2018,"lang":"en","type":"article","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer security; Computer science; Wireless; Wireless sensor network; Multitude; Boosting (machine learning); Risk analysis (engineering); Telecommunications; Business; Artificial intelligence; Computer network","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":[0.0001606505,0.0002565489,0.0002625708,0.0001260748,0.00003728949,0.00003285719,0.0001488438,0.0002361367,0.00003438766],"category_scores_gemma":[0.00001339209,0.0001854622,0.00004334517,0.0001501041,0.0001157116,0.00009808444,0.00007253778,0.0003185816,0.00005356632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001128026,"about_ca_system_score_gemma":0.00001025738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003632579,"about_ca_topic_score_gemma":0.0005190083,"domain_scores_codex":[0.9990286,0.00002156386,0.0001600779,0.0002687977,0.00009049905,0.0004305055],"domain_scores_gemma":[0.9994571,0.00007898659,0.00001825548,0.0003688427,0.00002192467,0.00005495711],"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":[0.0001622551,0.0003636873,0.009699764,0.0003484413,0.0005712876,0.0002859941,0.007511173,0.1940152,0.0219251,0.007635183,0.004995466,0.7524865],"study_design_scores_gemma":[0.0007616869,0.0003514074,0.02690823,0.0001321754,0.00001103221,0.00007099644,0.001414839,0.932544,0.03133736,0.002043019,0.003715863,0.0007094229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877083,0.001617106,0.00003196755,0.0004204209,0.00009859711,0.0001844042,0.000006193738,0.001302522,0.008630497],"genre_scores_gemma":[0.9984543,0.001258832,0.00009781083,0.0000222115,0.00008474648,0.000014265,0.000001820269,0.00004082842,0.00002516074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7517771,"threshold_uncertainty_score":0.7562928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0140711505354701,"score_gpt":0.2268413809068051,"score_spread":0.2127702303713351,"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."}}