{"id":"W2151797366","doi":"10.1007/s11036-006-7326-7","title":"Signal threshold adaptation for vertical handoff in heterogeneous wireless networks","year":2006,"lang":"en","type":"article","venue":"Mobile Networks and Applications","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":224,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bell (Canada); University of Toronto","funders":"","keywords":"Computer science; Handover; Roaming; Computer network; Wireless network; Vertical handover; Heterogeneous network; Heterogeneous 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002029814,0.0002581714,0.0003009773,0.0000592076,0.0001698759,0.00009174991,0.000142477,0.0002531529,0.0000170229],"category_scores_gemma":[0.000001300066,0.0002801025,0.0000900872,0.0003092606,0.00009633222,0.0001037524,0.00004178425,0.0002800927,0.00000290211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008772442,"about_ca_system_score_gemma":0.00001180642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004084059,"about_ca_topic_score_gemma":0.0006585608,"domain_scores_codex":[0.9984607,0.0000235796,0.0004547888,0.0004046267,0.0001214986,0.0005348293],"domain_scores_gemma":[0.9993055,0.0001992858,0.00003496918,0.0003025163,0.00005223793,0.000105521],"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":[0.00003173791,0.0001053802,0.0008268137,0.00003155269,0.00001452502,0.000001245538,0.00001492829,0.9806871,0.00005709608,0.002310647,0.0005374763,0.01538151],"study_design_scores_gemma":[0.0008119904,0.00004848506,0.0009864355,0.00002349016,0.00003511327,0.000005949666,0.00001865796,0.9901496,0.0001040631,0.001401432,0.006127746,0.0002870395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1427058,0.005039123,0.8494202,0.0000165971,0.0001764509,0.002057791,0.00001902556,0.0002550051,0.0003099857],"genre_scores_gemma":[0.9931544,0.0003244103,0.0001538982,0.00004986565,0.001040803,0.005001168,0.0001910855,0.00005928584,0.00002507587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8504486,"threshold_uncertainty_score":0.9999651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006560546571891093,"score_gpt":0.2049947078581687,"score_spread":0.1984341612862776,"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."}}