{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00871636,0.001543925,0.001317053,0.001967878,0.0007689528,0.002042668,0.001664945,0.001075657,0.002098674],"category_scores_gemma":[0.02054594,0.0002762166,0.0006574237,0.001490406,0.0006737438,0.002346646,0.001269499,0.0009777015,0.0004493167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002245905,"about_ca_system_score_gemma":0.00172714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004354383,"about_ca_topic_score_gemma":0.001899881,"domain_scores_codex":[0.9941005,0.002548994,0.0003888941,0.0003415915,0.002083702,0.0005362782],"domain_scores_gemma":[0.9907927,0.005584748,0.0007757571,0.0006954701,0.00192045,0.0002308297],"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":[0.0004734515,0.0002761071,0.002390373,0.0001297213,0.00009517276,0.00007384869,0.00008340968,0.8515139,0.005982566,0.02976805,0.001141295,0.1080721],"study_design_scores_gemma":[0.00001191381,0.0001723832,0.0002824693,0.000007240832,0.00001387278,0.00002890706,0.00002226185,0.9963304,0.001025599,0.001726581,0.0003714341,0.000006915486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04815918,0.001149602,0.9444051,0.0001813651,0.00007036966,0.0003147458,0.0001241707,0.0007115365,0.004884006],"genre_scores_gemma":[0.7865065,0.0007073678,0.2102765,0.00006721881,0.00008718552,0.0004946073,0.000302938,0.000127522,0.001430221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00871636,"threshold_uncertainty_score":0.04609704,"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."}}