{"id":"W2112017000","doi":"10.1109/tvt.2007.900525","title":"A Service-Agent-Based Roaming Architecture for WLAN/Cellular Integrated Networks","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Authentication Protocols Security","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Roaming; Computer network; Computer science; Authentication (law); Overhead (engineering); Service (business); Cellular network; Wireless network; Service provider; Heterogeneous network; Computer security; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005092534,0.0002622178,0.000257066,0.0002705382,0.0005614268,0.001200665,0.001019142,0.0007490095,0.002116522],"category_scores_gemma":[0.0005046641,0.0001680554,0.0003063879,0.0002580039,0.0003897747,0.001166879,0.000621673,0.000727472,0.0009944253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005134069,"about_ca_system_score_gemma":0.0006134388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002733061,"about_ca_topic_score_gemma":0.003635216,"domain_scores_codex":[0.999749,0.0000761521,0.00002481911,0.00003210454,0.00008632703,0.00003167524],"domain_scores_gemma":[0.9998358,0.0000220661,0.00001498955,0.0000336067,0.00006359907,0.00002982634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003993947,0.0003518266,0.001709288,0.0002530602,0.0001263728,0.0009629754,0.0009062598,0.1119658,0.0678874,0.4350193,0.01830401,0.3621143],"study_design_scores_gemma":[0.00004918566,0.0002126656,0.0004754713,0.00002914654,0.00007181672,0.0004284912,0.0001137985,0.8795345,0.01291209,0.02600064,0.08012857,0.00004376307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01855314,0.0004543982,0.9653592,0.0004773037,0.0001451338,0.0001518401,0.0000317348,0.003168992,0.01165831],"genre_scores_gemma":[0.5602244,0.0005985867,0.415825,0.0002904198,0.00008618903,0.0002389045,0.0002669804,0.0001464067,0.02232318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002733061,"threshold_uncertainty_score":0.007080495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01161545226268733,"score_gpt":0.2553387976343027,"score_spread":0.2437233453716153,"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."}}