{"id":"W2125750876","doi":"10.1109/pdcat.2005.178","title":"Ontology-Based Clustering and Routing in Peer-to-Peer Networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Distributed hash table; Peer-to-peer; Overlay network; Ontology; Computer network; Distributed computing; Exploit; Overlay; Architecture; Hash table; Routing (electronic design automation); Cluster analysis; Routing table; Hash function; Routing protocol; World Wide Web; Computer security; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002427759,0.0004578042,0.001030733,0.001014365,0.002219682,0.001969242,0.00194255,0.001731277,0.0008339865],"category_scores_gemma":[0.006591767,0.0005626351,0.000635511,0.001930554,0.002059668,0.00456072,0.001825516,0.0009765872,0.0004331913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00159947,"about_ca_system_score_gemma":0.00212002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005450148,"about_ca_topic_score_gemma":0.004634332,"domain_scores_codex":[0.9980106,0.0008103517,0.0001105993,0.0003450558,0.0005981793,0.0001251832],"domain_scores_gemma":[0.9973856,0.001183145,0.0002894746,0.000647022,0.0003558981,0.0001388957],"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":[0.00009701816,0.0001335644,0.00125626,0.0002787603,0.000104737,0.000271166,0.0006422651,0.6357864,0.01006563,0.2280805,0.0042133,0.1190705],"study_design_scores_gemma":[0.00004491976,0.00006219184,0.0005322369,0.00001947972,0.00003491302,0.0001537027,0.0001935351,0.8117894,0.00479508,0.1693781,0.01294387,0.00005253411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02923228,0.0006324396,0.9642896,0.000820033,0.0000837258,0.0001442639,0.00006114531,0.0006392346,0.004097247],"genre_scores_gemma":[0.4926814,0.001501942,0.5010122,0.0001921915,0.000148508,0.0002865023,0.0002703813,0.0001301521,0.003776704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005450148,"threshold_uncertainty_score":0.01283938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01559649343174631,"score_gpt":0.2573568253738768,"score_spread":0.2417603319421305,"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."}}