{"id":"W4320015708","doi":"10.1109/tcomm.2023.3240440","title":"Lightweight Flexible Group Authentication Utilizing Historical Collaboration Process Information","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Natural Science Foundation of China","keywords":"Process (computing); Computer science; Authentication (law); Group (periodic table); Computer network; Embedded system; Engineering; Computer security; Operating system","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002605511,0.0001955246,0.0001712145,0.0004780816,0.0005721553,0.0001200114,0.0005550097,0.0001604907,0.00004376063],"category_scores_gemma":[0.00001151184,0.0002250072,0.00008399748,0.002083049,0.0000487151,0.001068508,0.000004431111,0.000427384,0.0008180761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006570147,"about_ca_system_score_gemma":0.00005291342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001692187,"about_ca_topic_score_gemma":0.0001283492,"domain_scores_codex":[0.9986877,0.00008049396,0.0004698494,0.0001520575,0.000300779,0.0003090651],"domain_scores_gemma":[0.9982749,0.0001553291,0.00007327482,0.001205573,0.0001762873,0.0001146419],"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":[0.0000137745,0.0001371468,0.000009350899,0.00008040595,0.00007618007,5.572976e-7,0.002449675,0.9718978,0.001662127,0.0018692,0.006112835,0.01569095],"study_design_scores_gemma":[0.0003146478,0.0000395808,0.0001564063,0.00005731374,0.00006026358,0.000004986598,0.0004407392,0.9226602,0.003429274,0.0005088687,0.07204241,0.0002853224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02440532,0.0004453515,0.9495415,0.003939325,0.002176034,0.001344618,0.0001042195,0.006723087,0.01132052],"genre_scores_gemma":[0.9963429,0.000836562,0.001539428,0.00005867833,0.00004013717,0.0005198595,0.000240128,0.00004443669,0.0003778469],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9719376,"threshold_uncertainty_score":0.9999599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02182675359350712,"score_gpt":0.2588762021408052,"score_spread":0.2370494485472981,"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."}}