{"id":"W2160105108","doi":"10.1109/icc.2005.1494342","title":"Performance evaluation framework for vertical handoff algorithms in heterogeneous networks","year":2005,"lang":"en","type":"article","venue":"","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Handover; Quality of service; Computer network; Heterogeneous network; Wireless network; Underlay; Vertical handover; Wireless; Next-generation network; Cellular network; Bandwidth (computing); Distributed computing; Telecommunications; The Internet","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":[0.000713866,0.0002209123,0.0002541576,0.00006606605,0.000062067,0.00004713064,0.0001551084,0.0002936708,0.0002157346],"category_scores_gemma":[0.00007090802,0.0002242927,0.00008729746,0.0002084197,0.00003619187,0.000213348,0.00003643469,0.0003409839,0.00003383869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003248577,"about_ca_system_score_gemma":0.0000199982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006130909,"about_ca_topic_score_gemma":0.000171183,"domain_scores_codex":[0.9984089,0.00004563086,0.0003930484,0.0002939867,0.0002865369,0.0005718627],"domain_scores_gemma":[0.9992542,0.0002178666,0.00001656672,0.0003342543,0.0000765006,0.0001006263],"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":[0.00005374204,0.00005654694,0.001107173,0.0000275297,0.00002033294,7.111204e-7,0.0001177264,0.8834623,0.00001397203,0.0001946399,0.0002348736,0.1147105],"study_design_scores_gemma":[0.001064895,0.00006492978,0.002238882,0.00004361745,0.00003026757,0.000005501376,0.000007527772,0.9934093,0.00116972,0.0005685401,0.001135026,0.0002618074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6480607,0.001438611,0.3473557,0.00006913981,0.001015534,0.0009949444,0.000002853683,0.0002944433,0.0007680766],"genre_scores_gemma":[0.9841565,0.0001384848,0.01424971,0.0001448616,0.0009271764,0.0002931917,0.00002213702,0.00004629992,0.00002162655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3360958,"threshold_uncertainty_score":0.9146392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169870629746066,"score_gpt":0.2636708233918897,"score_spread":0.2466837604172831,"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."}}