{"id":"W2002365903","doi":"10.1109/35.1000224","title":"DiffServ resource allocation for fast handoff in wireless mobile internet","year":2002,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Langley Research Center","keywords":"Computer science; Computer network; Handover; Quality of service; Wireless network; Resource allocation; Call Admission Control; Mobile QoS; Wireless; Mobile IP; The Internet; Service (business); Service provider; 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":[0.0003294603,0.0002152821,0.0002707278,0.0001463977,0.0000960004,0.00006048398,0.0009449902,0.0001410875,0.00007888577],"category_scores_gemma":[0.00003274562,0.0002491838,0.00008447247,0.000403145,0.000123682,0.0002011142,0.0001574579,0.0003760627,0.0001531369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000215989,"about_ca_system_score_gemma":0.00000682989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002890125,"about_ca_topic_score_gemma":0.00137919,"domain_scores_codex":[0.9987019,0.0001134021,0.0004894158,0.0002399886,0.0001251793,0.0003301397],"domain_scores_gemma":[0.9975034,0.000320056,0.0000708329,0.001938236,0.00009253934,0.00007494231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003277145,0.006017505,0.009027644,0.001594619,0.0004932423,0.00001023474,0.02138351,0.2338607,0.02985745,0.01296834,0.3837877,0.3006713],"study_design_scores_gemma":[0.001206882,0.0000539518,0.00111249,0.00008962693,0.00002395964,0.000004664573,0.00006899171,0.8595991,0.000794352,0.0002510297,0.1365078,0.0002871357],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8566401,0.01395673,0.085444,0.002109089,0.002225652,0.005467125,0.000205646,0.001943034,0.03200864],"genre_scores_gemma":[0.9949867,0.0008040734,0.001402164,0.0000809089,0.0001426034,0.001059407,0.000174242,0.00006138664,0.001288495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6257384,"threshold_uncertainty_score":0.9999961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02518729115377509,"score_gpt":0.2461928462476948,"score_spread":0.2210055550939197,"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."}}