{"id":"W2108293981","doi":"10.1145/774749.774759","title":"Efficient micro-mobility using intra-domain multicast-based mechanisms (M&M)","year":2002,"lang":"en","type":"article","venue":"ACM SIGCOMM Computer Communication Review","topic":"IPv6, Mobility, Handover, Networks, Security","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Handover; Computer network; Multicast; Mobility management; Proxy Mobile IPv6; Mobile IP; Node (physics); Network packet; Scalability; Inter-domain; Mobility model; Packet loss; Distributed computing; Source-specific multicast","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":[0.001541851,0.0004933345,0.0008090508,0.0001046144,0.0002860514,0.0001035737,0.002173862,0.0001795393,0.0004421801],"category_scores_gemma":[0.0001290956,0.0005166256,0.0003091291,0.0006189976,0.0001594512,0.0001069326,0.0008294718,0.000730743,0.0002442848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003840726,"about_ca_system_score_gemma":0.00001957455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002805657,"about_ca_topic_score_gemma":0.00003152646,"domain_scores_codex":[0.9965082,0.001002564,0.001088718,0.0004792335,0.0003671994,0.0005541301],"domain_scores_gemma":[0.9930677,0.0007973702,0.0002222656,0.005519592,0.0001952885,0.0001977504],"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":[0.00005364548,0.005565329,0.0005663715,0.02272718,0.000715141,0.00002565283,0.002970923,0.6136147,0.008064177,0.005173242,0.03124667,0.3092769],"study_design_scores_gemma":[0.0007870366,0.00003411894,0.0001418275,0.002428363,0.0001232553,0.00002495817,0.00000689803,0.9598716,0.0002884454,0.0006956368,0.03494627,0.0006515927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.062499,0.1957424,0.7340543,0.001992584,0.0009322048,0.003059079,0.00003607314,0.001278225,0.0004061463],"genre_scores_gemma":[0.4506162,0.01013843,0.536268,0.002504992,0.0001071577,0.0001547934,0.00009667641,0.0001057873,0.000007970522],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3881172,"threshold_uncertainty_score":0.9997286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04355580001479402,"score_gpt":0.2667041256848755,"score_spread":0.2231483256700815,"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."}}