{"id":"W2104727936","doi":"10.1109/wcnc.2007.600","title":"Efficient Handoff Scheme for Heterogeneous IPv6-based Wireless Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Royal College of Anaesthetists","keywords":"Computer network; Handover; Computer science; Mobility management; Quality of service; Next-generation network; Overhead (engineering); Mobile IP; Packet loss; Wireless network; Network packet; Wireless; Distributed computing; The Internet; 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":[0.0005868381,0.000316211,0.0003899206,0.0005104949,0.0006160763,0.0003994316,0.0009387222,0.0003921097,0.0007312036],"category_scores_gemma":[0.0007201926,0.0001265322,0.0002400409,0.0003135352,0.0002751332,0.0007538325,0.0006172627,0.0003809626,0.00016025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003547639,"about_ca_system_score_gemma":0.0002714767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008188631,"about_ca_topic_score_gemma":0.0009424687,"domain_scores_codex":[0.9997261,0.00005530164,0.00002547154,0.00003572381,0.0001047413,0.00005252433],"domain_scores_gemma":[0.9997003,0.00006053064,0.0000475758,0.00007231221,0.00008535416,0.00003394189],"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":[0.001651725,0.000362151,0.004293417,0.0003115287,0.0001887402,0.001091736,0.0005166334,0.1587588,0.2883708,0.03227809,0.004699573,0.5074767],"study_design_scores_gemma":[0.0001659811,0.0006969026,0.002776838,0.0000178595,0.0001344002,0.0007011551,0.0001253526,0.9417208,0.04079614,0.006073387,0.006728287,0.00006288935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3110887,0.001416471,0.6824861,0.00014946,0.0002351754,0.0001712025,0.00009274446,0.001053896,0.003306268],"genre_scores_gemma":[0.9385164,0.0002903189,0.05967309,0.00003953689,0.00003468482,0.00004386764,0.0001322591,0.00001338104,0.001256378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009387222,"threshold_uncertainty_score":0.003103554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007884250584094858,"score_gpt":0.2179456851609435,"score_spread":0.2100614345768487,"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."}}