{"id":"W2101688718","doi":"10.1155/2013/143024","title":"The RSU Access Problem Based on Evolutionary Game Theory for VANET","year":2013,"lang":"en","type":"article","venue":"International Journal of Distributed Sensor Networks","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Vehicular ad hoc network; Bandwidth (computing); Competition (biology); Throughput; Computer network; Game theory; Evolutionarily stable strategy; Evolutionary game theory; Nash equilibrium; Wireless ad hoc network; Telecommunications; Wireless; Mathematical optimization; Microeconomics; Ecology","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":[0.001201279,0.0009674536,0.001166037,0.0007831383,0.0009742912,0.001700082,0.001985105,0.002066354,0.002616121],"category_scores_gemma":[0.003727325,0.000418628,0.001108636,0.00108166,0.001798799,0.002442326,0.001579271,0.001811158,0.0001988253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001565827,"about_ca_system_score_gemma":0.001203409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006332407,"about_ca_topic_score_gemma":0.003429767,"domain_scores_codex":[0.9987932,0.0006082575,0.00004791873,0.0001852722,0.0002048183,0.0001604837],"domain_scores_gemma":[0.9986889,0.000878802,0.0001233794,0.00003877057,0.0001361739,0.0001340595],"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":[0.00004414482,0.0000504855,0.0006684114,0.0001009883,0.00006373748,0.0004349116,0.000222061,0.6648339,0.0009911706,0.3211343,0.001868604,0.009587408],"study_design_scores_gemma":[0.00001521737,0.00003155716,0.0001288963,0.00001244174,0.00001280314,0.00009062561,0.00007722907,0.9008886,0.0001355741,0.09700485,0.001585298,0.00001686174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03499958,0.0007201404,0.9478649,0.001082627,0.00011951,0.0001701089,0.0001179603,0.0000470061,0.01487822],"genre_scores_gemma":[0.8993988,0.001427131,0.08534736,0.0003282408,0.0001554895,0.000470894,0.0001668386,0.00004231056,0.01266288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006332407,"threshold_uncertainty_score":0.01259106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007145465085040903,"score_gpt":0.2326919285359215,"score_spread":0.2255464634508806,"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."}}