{"id":"W2158962077","doi":"10.1109/vetecf.2005.1559020","title":"Load sharing with buffering over heterogeneous networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Computer network; UMTS frequency bands; Heterogeneous network; Radio resource management; Wireless network; Radio access network; Roaming; Wireless WAN; Cellular network; Wi-Fi; UMTS Terrestrial Radio Access Network; Wireless; Distributed computing; Wi-Fi array; Base station; Telecommunications; Mobile station","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":[0.001516341,0.00129085,0.0009693377,0.001099094,0.001322137,0.00228889,0.003313898,0.00126305,0.00275227],"category_scores_gemma":[0.004156048,0.000454883,0.000610498,0.001135548,0.001463608,0.0040296,0.002226689,0.0007495257,0.000394015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002890463,"about_ca_system_score_gemma":0.0007747458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002888798,"about_ca_topic_score_gemma":0.00153011,"domain_scores_codex":[0.9989335,0.0002674753,0.00004372998,0.000246012,0.0002382894,0.0002710138],"domain_scores_gemma":[0.9979396,0.001068264,0.0003012048,0.0002633112,0.0002658676,0.0001616461],"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":[0.0003234673,0.0001308264,0.001148777,0.00009385959,0.00005552439,0.0004425328,0.0002833827,0.868327,0.01097557,0.0701699,0.001816266,0.04623307],"study_design_scores_gemma":[0.00001387478,0.00004188534,0.00008317084,0.000006616577,0.00001681728,0.00004627887,0.00002818361,0.9867519,0.001498968,0.01072628,0.000769807,0.00001615502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1190154,0.001544592,0.8688379,0.0005096517,0.0001843057,0.0001531572,0.0001012409,0.001038252,0.008615488],"genre_scores_gemma":[0.9776424,0.0004518356,0.01901125,0.0001252239,0.0001152714,0.00007304744,0.00004945612,0.0000543673,0.002477176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003313898,"threshold_uncertainty_score":0.02097189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01379763295239419,"score_gpt":0.2452202071164694,"score_spread":0.2314225741640752,"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."}}