{"id":"W4245717026","doi":"10.32920/ryerson.14649684.v1","title":"Mobility Management Framework of Local Mobility","year":2021,"lang":"en","type":"preprint","venue":"","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Royal College of Anaesthetists; U.S. Department of Energy","keywords":"Mobility management; Computer science; Node (physics); Computer network; Software deployment; Implementation; Mobility model; Mobile IP; The Internet; Mobile computing; Distributed computing; World Wide Web; Engineering; Operating system; Software engineering","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":[0.003725015,0.001314429,0.0008646016,0.002290855,0.001585855,0.003628615,0.003043079,0.002086316,0.008450883],"category_scores_gemma":[0.004719572,0.0006025448,0.001334016,0.001623102,0.001411559,0.00395511,0.003454301,0.003248275,0.006817863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001694061,"about_ca_system_score_gemma":0.002643255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003557998,"about_ca_topic_score_gemma":0.002114378,"domain_scores_codex":[0.9967097,0.001162078,0.0003078872,0.0003982528,0.001089093,0.0003330508],"domain_scores_gemma":[0.998657,0.0002631379,0.0001575624,0.0003535131,0.0004250787,0.0001436377],"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":[0.00004678802,0.00005426057,0.0002918011,0.000227953,0.00005046232,0.000234187,0.000344123,0.006499846,0.002552822,0.8525615,0.02947337,0.1076628],"study_design_scores_gemma":[0.00005281,0.00008837021,0.0002942815,0.0002230713,0.00007349801,0.0005066731,0.0001151874,0.0596752,0.002930064,0.1744143,0.7615476,0.00007883817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008341562,0.00204368,0.955925,0.001145976,0.0005356679,0.0005258971,0.0006232812,0.005189566,0.03317672],"genre_scores_gemma":[0.08749327,0.004914265,0.8608578,0.001145838,0.001027653,0.002658045,0.003883762,0.0009951808,0.03702421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008450883,"threshold_uncertainty_score":0.02827108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009117815375296144,"score_gpt":0.2326212119480597,"score_spread":0.2235033965727635,"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."}}