{"id":"W2739965243","doi":"10.1109/access.2017.2733380","title":"Performance Improvement of Cluster-Based Routing Protocol in VANET","year":2017,"lang":"en","type":"article","venue":"IEEE Access","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":132,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Computer network; Routing protocol; Throughput; Vehicular ad hoc network; Overhead (engineering); Wireless ad hoc network; Network topology; Distributed computing; Routing (electronic design automation); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000263524,0.0001453048,0.0001951719,0.00006569597,0.00007455127,0.0001122444,0.0007120949,0.00007339141,0.00002203975],"category_scores_gemma":[0.00001510489,0.0001438092,0.00003717321,0.0000658637,0.00003302038,0.0004466015,0.00007935085,0.0001767322,0.000008236194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007104116,"about_ca_system_score_gemma":0.00002565614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001007978,"about_ca_topic_score_gemma":0.0002109926,"domain_scores_codex":[0.999027,0.00001067887,0.0003091885,0.0001592049,0.0001725388,0.0003214351],"domain_scores_gemma":[0.9991851,0.00002127409,0.0001295538,0.0005876316,0.00002933579,0.00004703017],"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":[0.00002290261,0.00002677639,0.03223384,0.0003376033,0.00001030782,0.000005430423,0.0000298469,0.9510756,0.003095938,0.000002029388,0.0002601677,0.01289956],"study_design_scores_gemma":[0.001161098,0.00004773821,0.0274101,0.0001955482,0.000004653829,7.457361e-7,0.000002360025,0.9087822,0.06159811,0.000008237869,0.0006281048,0.0001610668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785318,0.000003433717,0.001611998,0.00002321329,0.0002817776,0.01666917,0.000003200023,0.00008440956,0.002791044],"genre_scores_gemma":[0.9877596,0.000001188756,0.0001846061,0.00003271287,0.0001066099,0.01186408,0.000002192753,0.00003098087,0.00001805846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05850217,"threshold_uncertainty_score":0.5864369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02087108835843668,"score_gpt":0.2938703238889874,"score_spread":0.2729992355305507,"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."}}