{"id":"W4311511319","doi":"10.18280/i2m.210503","title":"Markov Renewal Prediction and Radial Kronecker Neural Network Based Handover for Seamless Mobility","year":2022,"lang":"en","type":"article","venue":"Instrumentation Mesure Métrologie","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Handover; Computer science; Markov chain; Computer network; Quality of service; Kronecker delta; Wireless network; Markov model; Node (physics); Markov process; Real-time computing; Wireless; Distributed computing; Engineering; Telecommunications; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005074832,0.0003608425,0.0003743526,0.0002175755,0.000274418,0.0004285075,0.000792376,0.0005212585,0.0006980055],"category_scores_gemma":[0.0009948569,0.0001830794,0.0003706012,0.0002484548,0.0003750749,0.0006484205,0.0003510974,0.0007197051,0.0001243753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007600413,"about_ca_system_score_gemma":0.0007076905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01210047,"about_ca_topic_score_gemma":0.008318779,"domain_scores_codex":[0.9997662,0.00006127227,0.00001177306,0.00004856678,0.00006325857,0.00004890841],"domain_scores_gemma":[0.9997472,0.000109285,0.0000394236,0.0000198463,0.00006953628,0.00001471547],"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":[0.0000605354,0.00003605225,0.001136532,0.00002417707,0.00002070846,0.00006286497,0.00004045747,0.9599835,0.002244918,0.004933718,0.0003385699,0.03111793],"study_design_scores_gemma":[0.000001033252,0.000009881527,0.00007789877,9.214756e-7,0.000002064068,0.000005125266,0.000001785751,0.9992772,0.0002116478,0.000374711,0.00003597462,0.000001668262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0914222,0.0004816616,0.90413,0.0002233274,0.00006584946,0.00003075751,0.00004008258,0.0003323703,0.003273727],"genre_scores_gemma":[0.9742669,0.0001988588,0.02305611,0.00004610321,0.00001359266,0.00003013082,0.00004898603,0.0000101702,0.002329065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01210047,"threshold_uncertainty_score":0.02406007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01364072269724732,"score_gpt":0.2349478449023368,"score_spread":0.2213071222050895,"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."}}