{"id":"W2469954218","doi":"10.1109/tmc.2016.2585106","title":"Network Coding as a Performance Booster for Concurrent Multi-Path Transfer of Data in Multi-Hop Wireless Networks","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Computer network; Linear network coding; Network packet; Transport layer; Stream Control Transmission Protocol; Testbed; Wireless network; Distributed computing; Network layer; Wireless; Layer (electronics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001216898,0.0003949295,0.0003381537,0.0006534287,0.0004851394,0.0005289241,0.0008279829,0.000511696,0.0007282933],"category_scores_gemma":[0.004853955,0.000159109,0.00017043,0.0005370242,0.0008956578,0.001285194,0.0009640693,0.0009462937,0.0001551339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006995052,"about_ca_system_score_gemma":0.0006904079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001677457,"about_ca_topic_score_gemma":0.001545893,"domain_scores_codex":[0.9994122,0.000185643,0.0000227436,0.00006033709,0.0002567002,0.00006239946],"domain_scores_gemma":[0.9972252,0.001710318,0.0002204756,0.0002645592,0.0004980811,0.00008133929],"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":[0.0004117386,0.000240086,0.001668979,0.0001618341,0.00003404574,0.000235049,0.0003111704,0.5958691,0.07491287,0.07193703,0.001879373,0.2523388],"study_design_scores_gemma":[0.000007845209,0.00009009958,0.0001395584,0.000008407439,0.000007447882,0.0000608428,0.00001507271,0.9851917,0.008005183,0.005794427,0.0006677802,0.00001152231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08934602,0.001163502,0.9046007,0.0005228085,0.0001121346,0.00007743216,0.00002433998,0.0008056645,0.003347329],"genre_scores_gemma":[0.9220762,0.0004592437,0.07626745,0.0001014392,0.00006057061,0.00005332624,0.00002386137,0.00004694925,0.0009108955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001677457,"threshold_uncertainty_score":0.006435692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09436529703555026,"score_gpt":0.3288500961123661,"score_spread":0.2344847990768159,"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."}}