{"id":"W3082525356","doi":"10.1109/access.2020.3019795","title":"Trusted Orchestration for Smart Decision-Making in Internet of Vehicles","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Ministry of Science and ICT, South Korea; King Saud University; National Research Foundation","keywords":"Computer science; Analytic hierarchy process; The Internet; Process (computing); Decision-making; Robustness (evolution); Situation awareness; Data mining; Computer security; Operations research; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004714309,0.0005792709,0.0008352848,0.0009462725,0.001599959,0.003500723,0.001645742,0.001168722,0.001852701],"category_scores_gemma":[0.00753116,0.0003886653,0.0007903926,0.0008899032,0.002023158,0.002778755,0.002877698,0.001439861,0.0003095982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001845796,"about_ca_system_score_gemma":0.003950081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005408864,"about_ca_topic_score_gemma":0.0044175,"domain_scores_codex":[0.9954052,0.002181079,0.0002901216,0.0006149148,0.001028378,0.0004803414],"domain_scores_gemma":[0.9970691,0.001474988,0.0004470356,0.0002938653,0.0005145941,0.0002004829],"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":[0.0002369086,0.0001308104,0.00219268,0.0002368013,0.0001176906,0.0004879549,0.0009736077,0.7334681,0.00344974,0.201917,0.001179897,0.05560879],"study_design_scores_gemma":[0.00001814764,0.00006338621,0.0001823169,0.00003011248,0.00002268217,0.00004188302,0.0002344596,0.9279811,0.001051701,0.06772729,0.002628277,0.0000187138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04143437,0.000293349,0.9475381,0.000823591,0.00008645205,0.0001640525,0.00005036926,0.0003257261,0.009284035],"genre_scores_gemma":[0.9237157,0.0002232078,0.0742496,0.00007841131,0.00003420653,0.000114721,0.0000543963,0.00002773002,0.001502043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005408864,"threshold_uncertainty_score":0.02493197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03177710265780563,"score_gpt":0.2873622196579244,"score_spread":0.2555851170001188,"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."}}