{"id":"W2081605040","doi":"10.4236/ijcns.2012.512084","title":"A Scalable and Robust DHT Protocol for Structured P2P Network","year":2012,"lang":"en","type":"article","venue":"International Journal of Communications Network and System Sciences","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Distributed hash table; Computer science; Latency (audio); Computer network; Hash table; Scalability; Liveness; Routing protocol; Routing table; Distributed computing; Zone Routing Protocol; Enhanced Interior Gateway Routing Protocol; Lookup table; Peer-to-peer; Dynamic Source Routing; Routing (electronic design automation); Hash function; Computer security; Operating system","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":[0.001149461,0.0003843894,0.0006485559,0.0007676087,0.0008126965,0.001022158,0.001697737,0.0006419824,0.001841983],"category_scores_gemma":[0.003257248,0.0003212203,0.000389918,0.0009807845,0.0006294691,0.002139074,0.00145596,0.000872068,0.0007143809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006948172,"about_ca_system_score_gemma":0.0009009216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001258355,"about_ca_topic_score_gemma":0.001194304,"domain_scores_codex":[0.9991148,0.0001576671,0.00007957709,0.0001181068,0.0004783308,0.0000515754],"domain_scores_gemma":[0.9987053,0.0003125536,0.0001309704,0.0004325997,0.0003373013,0.00008134574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008230314,0.0002837454,0.002236781,0.001303548,0.0002288069,0.00128055,0.0006002363,0.11334,0.1358753,0.05488884,0.03165187,0.6574875],"study_design_scores_gemma":[0.000483316,0.001095891,0.001948122,0.00009242574,0.0002296878,0.002750002,0.000427048,0.7089117,0.1053816,0.03953828,0.1389228,0.0002191167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01957246,0.001185726,0.9689095,0.0004066063,0.0002692706,0.000670862,0.000664416,0.004914515,0.003406694],"genre_scores_gemma":[0.4469866,0.001523541,0.5405499,0.0002612192,0.0002383378,0.0007629698,0.002861079,0.0003863222,0.006430066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001841983,"threshold_uncertainty_score":0.006162107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06644405462662982,"score_gpt":0.3443607707751182,"score_spread":0.2779167161484884,"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."}}