{"id":"W2096199330","doi":"10.1109/iwqos.2007.376546","title":"On the Resilience-Complexity Tradeoff of Network Coding in Dynamic P2P Networks","year":2007,"lang":"en","type":"article","venue":"International Workshop on Quality of Service","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Linear network coding; Computer science; Coding (social sciences); Resilience (materials science); Theoretical computer science; Computational complexity theory; Distributed computing; Computer network; Algorithm; Mathematics","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":[0.002311694,0.0005677787,0.0005022106,0.0009804645,0.000682168,0.0009498444,0.000641613,0.001083411,0.001174077],"category_scores_gemma":[0.02252586,0.0003186487,0.0003506352,0.0007702209,0.002349984,0.002870989,0.001182801,0.001063717,0.0001117612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002059355,"about_ca_system_score_gemma":0.0007029555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002284924,"about_ca_topic_score_gemma":0.001271312,"domain_scores_codex":[0.9988911,0.0005031082,0.00003046195,0.00009480859,0.0003146834,0.0001658064],"domain_scores_gemma":[0.9722937,0.02511453,0.001021463,0.0007107446,0.0006283124,0.0002311774],"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":[0.0001197152,0.00003527615,0.0008987451,0.00007484616,0.00001926944,0.0001246565,0.0001753829,0.8523899,0.006603829,0.1292158,0.0004148007,0.00992775],"study_design_scores_gemma":[0.00001064842,0.0000531669,0.0004468172,0.00001650214,0.00000870341,0.00008211672,0.00004487771,0.9501483,0.001610037,0.04727729,0.0002841237,0.00001733907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3411077,0.001837053,0.6374156,0.00322083,0.00008250256,0.00008021139,0.000145535,0.0002367211,0.01587391],"genre_scores_gemma":[0.9782724,0.0006557642,0.02024002,0.00007329744,0.00004157704,0.00004510198,0.00002291747,0.00003178921,0.0006170424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002311694,"threshold_uncertainty_score":0.01494175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1036516254987189,"score_gpt":0.370040041402382,"score_spread":0.2663884159036631,"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."}}