{"id":"W2945400041","doi":"10.1016/j.comnet.2019.05.008","title":"Coded multicasting in cache-enabled vehicular ad hoc network","year":2019,"lang":"en","type":"article","venue":"Computer Networks","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"Computer science; Multicast; Computer network; Wireless ad hoc network; Cache; Vehicular ad hoc network; Source-specific multicast; Distributed computing; Wireless","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006307506,0.0003190706,0.000666588,0.0008950018,0.0007817534,0.0006810231,0.001090826,0.0005767648,0.0006248391],"category_scores_gemma":[0.002589028,0.0002214886,0.0001876752,0.001121614,0.000456342,0.0008342178,0.0005397034,0.0003875888,0.00009719554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00130952,"about_ca_system_score_gemma":0.0009956345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008496331,"about_ca_topic_score_gemma":0.00994164,"domain_scores_codex":[0.9995142,0.0001435814,0.00002162978,0.00005466636,0.0001527405,0.0001130751],"domain_scores_gemma":[0.9981839,0.0008345006,0.000120732,0.0001804859,0.0006183411,0.00006198525],"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":[0.0008998957,0.0001827794,0.00372641,0.0003130654,0.0001019087,0.000937074,0.000446786,0.7330589,0.04230903,0.07924992,0.00598836,0.1327858],"study_design_scores_gemma":[0.000008692507,0.00005694667,0.0001896154,0.000008661095,0.00001735664,0.0001061096,0.00004244314,0.9910446,0.002961079,0.004803456,0.0007501124,0.00001085135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4127597,0.002607719,0.5760472,0.000549975,0.0002835718,0.0001003262,0.0002776943,0.0007480643,0.00662577],"genre_scores_gemma":[0.979006,0.0003033549,0.01891032,0.00003471818,0.00002891268,0.00001850039,0.00007349552,0.00001564804,0.001609024],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008496331,"threshold_uncertainty_score":0.0168938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01063141649255198,"score_gpt":0.2028021002885553,"score_spread":0.1921706837960033,"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."}}