{"id":"W4250251176","doi":"10.1002/wcm.465","title":"Introducing reliability and load balancing in mobile IPv6‐based networks","year":2006,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Computer science; Mobile IP; Computer network; Load balancing (electrical power); IPv6; Node (physics); Distributed computing; Reliability (semiconductor); Workload; Mobile computing; Operating system; The Internet","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":[0.001195559,0.0002856907,0.0004294261,0.0001048477,0.0003594431,0.0001259532,0.000428842,0.0001721201,0.000005788445],"category_scores_gemma":[0.00002527834,0.00032599,0.00005579015,0.0004245429,0.000245692,0.0001640809,0.0005016348,0.0006823128,0.000001388498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002703026,"about_ca_system_score_gemma":0.00003979333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000618064,"about_ca_topic_score_gemma":0.0009637265,"domain_scores_codex":[0.9980391,0.0002061859,0.0006564618,0.0004521701,0.0001562248,0.0004898461],"domain_scores_gemma":[0.9975467,0.0006859237,0.0001015518,0.001469503,0.0001079833,0.00008828556],"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":[0.000008538264,0.0001373084,0.03077259,0.0001470603,0.000009573154,0.000001573225,0.0005294468,0.9006152,0.0003126955,0.0002356,0.00007331625,0.06715716],"study_design_scores_gemma":[0.0006479542,0.00003565813,0.01068805,0.0001795284,0.00001589467,0.000006147073,0.0001805425,0.9848464,0.00008193667,0.0001310823,0.002869492,0.0003173863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9539868,0.01678953,0.02730218,0.00004305676,0.0002262304,0.0007251839,0.000006267486,0.0003518817,0.000568922],"genre_scores_gemma":[0.9934977,0.0009262495,0.005120556,0.00003497682,0.0001663698,0.0001574079,0.00004404943,0.0000459866,0.000006687927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08423118,"threshold_uncertainty_score":0.9999192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005262098147915495,"score_gpt":0.2192582242676955,"score_spread":0.2139961261197799,"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."}}