{"id":"W2050600060","doi":"10.1007/s11036-009-0168-3","title":"A Resilient and Scalable Flocking Scheme in Autonomous Vehicular Networks","year":2009,"lang":"en","type":"article","venue":"Mobile Networks and Applications","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; St. Francis Xavier University","funders":"","keywords":"Flocking (texture); Computer science; Vehicular ad hoc network; Wireless ad hoc network; Scalability; Correctness; Obstacle; Distributed computing; Collision; Computer network; Mobile ad hoc network; Wireless; Intelligent transportation system; Scheme (mathematics); Overhead (engineering); Computer security; Algorithm; Network packet; 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":[0.0002155152,0.000238382,0.0002714176,0.00008032734,0.0001629732,0.0001036693,0.0001316533,0.0001993756,0.00001147928],"category_scores_gemma":[0.000002438838,0.0002564308,0.0000410583,0.0004519241,0.00005815683,0.0001074364,0.00005080889,0.0004020159,0.000004565445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007020351,"about_ca_system_score_gemma":0.000009892808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001082709,"about_ca_topic_score_gemma":0.00004005125,"domain_scores_codex":[0.9986363,0.00002322445,0.0003248325,0.0003850732,0.00009975099,0.000530784],"domain_scores_gemma":[0.9993467,0.00005357683,0.00003770736,0.0003579252,0.00002364477,0.0001804536],"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":[0.000002913311,0.00003206506,0.0008090512,0.0000103567,0.00001093212,0.000004737893,0.00001391614,0.9547681,0.00007700524,0.0009236603,0.000574021,0.0427733],"study_design_scores_gemma":[0.000302784,0.00003361136,0.006058928,0.00005416308,0.00001475216,0.00001959055,0.00002079419,0.9592408,0.00001422113,0.0002246436,0.03375358,0.0002621149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5648725,0.04950904,0.37874,0.0001900941,0.0001532797,0.002744278,0.000006131724,0.0008425732,0.002942102],"genre_scores_gemma":[0.9958928,0.002221914,0.0006103868,0.0001480528,0.0003495071,0.0006536987,0.00003343593,0.00003688683,0.00005329081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4310203,"threshold_uncertainty_score":0.9999888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003430212024724805,"score_gpt":0.197253204162733,"score_spread":0.1938229921380082,"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."}}