{"id":"W2095805756","doi":"10.1109/twc.2009.080166","title":"Proposal and analysis of adaptive mobility management in ip-based mobile networks","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Computer network; Mobility management; Quality of service; Handover; Mobile IP; Node (physics); Network packet; Latency (audio); Mobility model; Distributed computing; 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":[0.0003435178,0.0002224451,0.0004235266,0.00047835,0.0001516162,0.00002363214,0.00048908,0.0001392892,0.00002372423],"category_scores_gemma":[0.000001100817,0.0002523476,0.0001682772,0.001665816,0.0002147003,0.0001395867,0.000006259841,0.000508418,0.000001621174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001886305,"about_ca_system_score_gemma":0.000021984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008523263,"about_ca_topic_score_gemma":0.001950192,"domain_scores_codex":[0.9985681,0.000195048,0.0005125497,0.0002761365,0.0001796492,0.0002684855],"domain_scores_gemma":[0.997848,0.0002493629,0.00006852518,0.001681134,0.0000723696,0.00008060845],"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":[0.00005681098,0.0009135399,0.0001401483,0.00002595704,0.0003426395,8.550887e-7,0.0002627467,0.9431971,0.0000654013,0.0005712866,0.00000608568,0.05441745],"study_design_scores_gemma":[0.0005690379,0.0001077759,0.01058475,0.00004559069,0.0005212862,3.902918e-7,0.0001515432,0.9870151,0.000578365,0.0001601491,0.00004912991,0.0002168337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2098179,0.00069221,0.7871487,0.00009321364,0.0001172003,0.001124101,0.00008676722,0.000242057,0.0006778945],"genre_scores_gemma":[0.9942868,0.0009178402,0.004333776,0.00003498953,0.000005879125,0.0003589402,0.00003056039,0.00001972938,0.00001143573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.784469,"threshold_uncertainty_score":0.9999928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01319679567126484,"score_gpt":0.2480784099356926,"score_spread":0.2348816142644277,"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."}}