{"id":"W3114954144","doi":"10.1109/iemcon51383.2020.9284953","title":"State-of-the-Art VANET Trust Models: Challenges and Recommendations","year":2020,"lang":"en","type":"article","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University of Edmonton","funders":"","keywords":"Computer science; Vehicular ad hoc network; Popularity; Computer security; Trust management (information system); Architecture; State (computer science); Blockchain; Wireless ad hoc network; Zero (linguistics); Computational trust; Telecommunications","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":[0.00005428143,0.00009060764,0.0001157363,0.00001469446,0.00002310155,0.0000097438,0.0001015903,0.00003112228,0.00007361415],"category_scores_gemma":[0.000007040326,0.00007420875,0.00002783776,0.00007033234,0.0000194333,0.0001081038,0.00004948915,0.0001148229,0.0000186877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001013583,"about_ca_system_score_gemma":0.000005660936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002058935,"about_ca_topic_score_gemma":0.00005909606,"domain_scores_codex":[0.9995158,0.00001867422,0.0001404709,0.0001098106,0.00007614725,0.0001390876],"domain_scores_gemma":[0.9997186,0.00003030621,0.0000156793,0.0001435537,0.00001389085,0.00007793672],"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":[0.000002054003,0.000005806043,0.0000118732,0.00004964548,0.00003559337,7.733649e-7,0.0007394719,0.9409945,0.00009305729,0.001768747,0.01561534,0.04068314],"study_design_scores_gemma":[0.0001316608,0.00001516417,0.0001101428,0.00001270038,0.000009297154,0.000002624042,0.00007726761,0.9457418,0.0002902826,0.001191658,0.05232605,0.00009137536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2605335,0.04813493,0.1767717,0.09193679,0.001980879,0.002395302,0.0001727031,0.003267902,0.4148063],"genre_scores_gemma":[0.9927047,0.004131858,0.002577192,0.0002364739,0.00004773174,0.000009292491,0.000009121991,0.00003034613,0.0002532922],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7321712,"threshold_uncertainty_score":0.3026145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02908606519438636,"score_gpt":0.20652825713781,"score_spread":0.1774421919434236,"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."}}