{"id":"W2139352451","doi":"10.1109/jsac.2008.080606","title":"Stochastic analysis of network coding in epidemic routing","year":2008,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Linear network coding; Computer network; Correctness; Routing protocol; Coding (social sciences); Distributed computing; Wireless network; Wireless; Network packet; Algorithm; Telecommunications","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":[0.002713284,0.0007248044,0.0008516163,0.001260273,0.0007168634,0.001398481,0.001008489,0.001380861,0.002001625],"category_scores_gemma":[0.0144063,0.0005380902,0.0007134981,0.0008909921,0.002423874,0.001885884,0.001348597,0.001375144,0.0002438912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002905261,"about_ca_system_score_gemma":0.001549114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008863493,"about_ca_topic_score_gemma":0.003975752,"domain_scores_codex":[0.9987769,0.0005872544,0.00003880991,0.00008687707,0.0003183297,0.0001918422],"domain_scores_gemma":[0.9914534,0.006403474,0.0007920189,0.0002630678,0.0008276467,0.0002603295],"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":[0.00002188085,0.00001287358,0.000375769,0.00003607618,0.00001670087,0.00008068442,0.00008320626,0.5790813,0.0006887349,0.4165285,0.0008058615,0.002268394],"study_design_scores_gemma":[0.000005520861,0.000005397545,0.00006815199,0.000007097571,0.000003468094,0.00001218348,0.00001497439,0.9422805,0.0000629409,0.05718079,0.0003516514,0.000007276418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06615888,0.001230884,0.9133627,0.001673435,0.0001400324,0.00008486586,0.0001875543,0.0001652388,0.01699636],"genre_scores_gemma":[0.9562528,0.001784961,0.03250635,0.0002765178,0.0001642491,0.0002685165,0.0001710691,0.0000875124,0.008487958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008863493,"threshold_uncertainty_score":0.02107924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06992630000424571,"score_gpt":0.3071814167100825,"score_spread":0.2372551167058368,"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."}}