{"id":"W3092706418","doi":"10.3991/ijim.v14i17.16639","title":"MROM Scheme to Improve Handoff Performance in Mobile Networks","year":2020,"lang":"en","type":"article","venue":"International Journal of Interactive Mobile Technologies (iJIM)","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministère des Ressources Naturelles et de la Faune","keywords":"Multihoming; Handover; Computer network; Computer science; Router; Mobile IP; Network packet; Routing protocol; Routing (electronic design automation); Throughput; Mobility management; Distributed computing; The Internet; Internet Protocol; Wireless; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003280931,0.0003718816,0.0005583803,0.0004754212,0.0000375838,0.0001309406,0.001345641,0.0002665496,0.0001130977],"category_scores_gemma":[0.0003659556,0.0003531395,0.0002173997,0.000498363,0.0001219994,0.0008418288,0.0005074839,0.001577713,0.00005254944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007761372,"about_ca_system_score_gemma":0.00004810693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008756643,"about_ca_topic_score_gemma":0.00002171126,"domain_scores_codex":[0.9976134,0.00004087457,0.0009845486,0.0003613594,0.000541201,0.0004586424],"domain_scores_gemma":[0.9984744,0.0002390589,0.0003290158,0.0002704358,0.0005617795,0.0001252658],"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":[0.002753714,0.0006481928,0.02058782,0.0001485298,0.001168242,0.0005752803,0.003681914,0.6175724,0.0440931,0.0001359722,0.005258407,0.3033764],"study_design_scores_gemma":[0.00588555,0.003933813,0.005802508,0.00122918,0.00007584539,0.0003292706,0.006788156,0.6888233,0.2168255,0.000562163,0.06811737,0.001627317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817203,0.001958669,0.01086786,0.0005561755,0.003124685,0.0006832264,0.00003110874,0.0004887683,0.0005692235],"genre_scores_gemma":[0.9968754,0.0008901164,0.001195236,0.000222124,0.0005188744,0.0002183526,0.00000658028,0.00005350229,0.00001979237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3017491,"threshold_uncertainty_score":0.9998921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007197987789501192,"score_gpt":0.2392746204787338,"score_spread":0.2320766326892326,"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."}}