{"id":"W4407937491","doi":"10.1109/tmc.2025.3545444","title":"Vehicle-Assisted Service Caching for Task Offloading in Vehicular Edge Computing","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Computer science; Edge computing; Task (project management); Mobile edge computing; Computer network; Service (business); Mobile computing; Server; Enhanced Data Rates for GSM Evolution; Distributed computing; Cloud computing; Operating system; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001179621,0.000455011,0.0005747226,0.0008160853,0.001243164,0.0003850767,0.001223332,0.0002215561,0.00000128148],"category_scores_gemma":[0.00002663285,0.000519833,0.0002843923,0.002331643,0.0000413043,0.0003981293,0.00005032731,0.0008299709,0.00002328624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003919464,"about_ca_system_score_gemma":0.0002139796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002736424,"about_ca_topic_score_gemma":0.00005137749,"domain_scores_codex":[0.9964431,0.0002283546,0.0009259324,0.001080551,0.000321014,0.001001071],"domain_scores_gemma":[0.9973646,0.001287153,0.0002246204,0.0007443913,0.0002418751,0.0001373671],"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":[0.00002512826,0.0002819326,0.0002611929,0.0002376612,0.00007259284,0.00001770132,0.001590791,0.6620982,0.00599193,0.0002047416,0.0002171598,0.3290009],"study_design_scores_gemma":[0.001431045,0.00009887368,0.0009555502,0.0008212097,0.00003093638,0.00001776445,0.00009791663,0.9867767,0.007334327,0.0001846204,0.001759436,0.0004916136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2736062,0.0001036328,0.7169959,0.0003063285,0.007549843,0.0006932419,0.000001188692,0.0004898167,0.0002538353],"genre_scores_gemma":[0.9732519,0.00000283812,0.02512985,0.001015762,0.0004471793,0.00004585029,0.000004005792,0.00004043565,0.00006214945],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6996457,"threshold_uncertainty_score":0.9997253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01663381487815505,"score_gpt":0.2727074205078433,"score_spread":0.2560736056296882,"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."}}