{"id":"W4210912760","doi":"10.1155/2022/5918128","title":"A Software-Defined Networking Roadside Unit Cloud Resource Management Framework for Vehicle Ad Hoc Networks","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Computer science; Cloud computing; Computer network; Software-defined networking; Wireless ad hoc network; Distributed computing; Vehicular ad hoc network; Integer programming; Wireless; Algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007562112,0.0005110282,0.0003761926,0.0002927506,0.0005700249,0.0008668858,0.001770282,0.0003911531,0.001288471],"category_scores_gemma":[0.000732309,0.0002254363,0.0004960972,0.0003355961,0.0003447882,0.0008819032,0.001097534,0.001035718,0.0003396738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008996662,"about_ca_system_score_gemma":0.002169736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008629721,"about_ca_topic_score_gemma":0.01466793,"domain_scores_codex":[0.9996173,0.00007720473,0.00002552382,0.00005017167,0.000148662,0.00008103519],"domain_scores_gemma":[0.9998019,0.00003538017,0.00002720641,0.00002944931,0.00006641709,0.00003974911],"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":[0.0001139361,0.0002222208,0.001194124,0.0001824826,0.00009913275,0.0003045217,0.0001592026,0.6230743,0.01092693,0.1791289,0.01830184,0.1662924],"study_design_scores_gemma":[0.00001346261,0.00003388314,0.0001021181,0.00001123756,0.00001163067,0.00003567412,0.00002182313,0.9788112,0.001380287,0.007236139,0.01233069,0.00001182388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008300784,0.0004733398,0.9829146,0.0002473029,0.0001350705,0.0001986331,0.0000987735,0.001769054,0.005862532],"genre_scores_gemma":[0.4091251,0.0008300169,0.5829274,0.0002163471,0.00007561603,0.0005500601,0.0005296431,0.0002695971,0.005476198],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008629721,"threshold_uncertainty_score":0.01715899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008646943006905099,"score_gpt":0.2223455436388212,"score_spread":0.2136986006319161,"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."}}