{"id":"W4394994526","doi":"10.1109/mnet.2024.3391767","title":"Generative AI-Enabled Vehicular Networks: Fundamentals, Framework, and Case Study","year":2024,"lang":"en","type":"article","venue":"IEEE Network","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Computer science; Generative grammar; Artificial intelligence; Machine learning","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005955743,0.0005643385,0.0005309461,0.0001067989,0.0002851825,0.0005976208,0.00019736,0.0003341932,0.00006552901],"category_scores_gemma":[0.00001017996,0.0005504022,0.0001376425,0.0008476108,0.00008700913,0.0003098034,0.0000948223,0.001214123,0.00008266788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001834327,"about_ca_system_score_gemma":0.00003307359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005560874,"about_ca_topic_score_gemma":0.0002537107,"domain_scores_codex":[0.9972534,0.0002004253,0.0005025236,0.0006952226,0.0003189674,0.00102946],"domain_scores_gemma":[0.9987218,0.0003060291,0.00003452146,0.0005654389,0.00004475175,0.0003274101],"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":[0.00001265916,0.00004647683,0.0005762005,0.00005960991,0.0005466791,0.01288928,0.0006931355,0.9199151,0.0000238523,0.0001342982,0.06257109,0.002531667],"study_design_scores_gemma":[0.0003594205,0.000162657,0.00009595419,0.0002823382,0.0002159067,0.002108134,0.000409495,0.9717156,0.00002365005,0.0009625999,0.02302924,0.0006349637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8603413,0.0461565,0.07460217,0.0001452962,0.01456892,0.00153548,0.00001178458,0.001948087,0.0006904348],"genre_scores_gemma":[0.9868579,0.0005250754,0.0009774397,0.000442775,0.01059657,0.00017965,0.0000153246,0.0002039127,0.0002013506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1265166,"threshold_uncertainty_score":0.9996948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01115945130372076,"score_gpt":0.2470944880513831,"score_spread":0.2359350367476623,"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."}}