{"id":"W3186696328","doi":"10.3390/electronics10131584","title":"Blockchain-Based Pseudonym Management Scheme for Vehicular Communication","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pseudonym; Vehicular ad hoc network; Computer science; Anonymity; Authentication (law); Scheme (mathematics); Computer security; Computer network; Wireless ad hoc network; Single point of failure; Public key infrastructure; Wireless; Public-key cryptography; Encryption; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001448258,0.0004730374,0.0009163185,0.0006698741,0.002012602,0.001072824,0.001797293,0.001222597,0.003600055],"category_scores_gemma":[0.00282212,0.0002274997,0.0003810116,0.001135041,0.001174168,0.003405159,0.002171358,0.0009815552,0.000738354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001508154,"about_ca_system_score_gemma":0.002809003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00278177,"about_ca_topic_score_gemma":0.002901993,"domain_scores_codex":[0.9980439,0.0005180759,0.000172293,0.0003602119,0.0006785784,0.0002270401],"domain_scores_gemma":[0.9978738,0.0005029901,0.0003559944,0.00052263,0.0005221119,0.0002224283],"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":[0.001642399,0.0005422892,0.003358101,0.0006479134,0.0001567456,0.001725488,0.001823182,0.3196777,0.05580325,0.3132147,0.01266594,0.2887422],"study_design_scores_gemma":[0.0003592759,0.0005426897,0.0005723211,0.00006537262,0.00005977719,0.00066661,0.0001443717,0.8870987,0.01377681,0.06999774,0.02660977,0.0001065786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05947248,0.0007220932,0.9280346,0.0006970411,0.0002934068,0.0006750072,0.0003284941,0.0008261587,0.008950723],"genre_scores_gemma":[0.9246435,0.0004335963,0.06662942,0.0001107426,0.00008712096,0.0004589564,0.0003430713,0.00002348689,0.007270209],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003600055,"threshold_uncertainty_score":0.01204342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006262231778306287,"score_gpt":0.2089684527913818,"score_spread":0.2027062210130755,"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."}}