{"id":"W1985838299","doi":"10.1504/ijcnds.2012.044320","title":"A seamless handover scheme for vehicles across heterogeneous networks","year":2011,"lang":"en","type":"article","venue":"International Journal of Communication Networks and Distributed Systems","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer network; Computer science; Handover; Network packet; Soft handover; Heterogeneous network; Packet loss; Mobility management; Overhead (engineering); Mobile IP; Wireless network; Wireless; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005613827,0.0003044292,0.000338998,0.0006070611,0.0007458033,0.000616479,0.0009519277,0.0007122712,0.0005749355],"category_scores_gemma":[0.0009242957,0.0001499556,0.0003085501,0.0003903891,0.0003738122,0.001023765,0.001373758,0.0006378687,0.0003272559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004837824,"about_ca_system_score_gemma":0.0003347145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001429438,"about_ca_topic_score_gemma":0.001540264,"domain_scores_codex":[0.9996015,0.0000726824,0.0000345837,0.00004653999,0.0001565026,0.00008827089],"domain_scores_gemma":[0.9996324,0.00005000361,0.00005467611,0.0001017067,0.00009504704,0.00006606497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007470217,0.0002162708,0.002917552,0.0003383856,0.0002458792,0.001276983,0.0009315225,0.05915798,0.2483418,0.0436984,0.006485946,0.6356423],"study_design_scores_gemma":[0.0002709101,0.00258137,0.007621912,0.00007186944,0.0003655952,0.003261403,0.0007149022,0.7393039,0.1228583,0.02686399,0.09578403,0.0003018778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1283385,0.001408924,0.8626674,0.0002927852,0.0002748811,0.0003467255,0.0001217733,0.001536439,0.005012709],"genre_scores_gemma":[0.8663014,0.000472655,0.1286811,0.0001024096,0.0000846578,0.0001047363,0.0002406404,0.00003879718,0.003973631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001429438,"threshold_uncertainty_score":0.003510118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02303948927825476,"score_gpt":0.2585587720696979,"score_spread":0.2355192827914431,"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."}}