{"id":"W2104025686","doi":"10.1109/icdcs.2008.45","title":"Optimized Multipath Network Coding in Lossy Wireless Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Computer network; Unicast; Linear network coding; Network packet; Retransmission; Multipath routing; Distributed computing; Multicast; Multiple description coding; Testbed; Network congestion; Routing protocol; Wireless network; Packet loss; Multipath propagation; Wireless; Wireless Routing Protocol; Telecommunications; Channel (broadcasting)","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":[0.0008235917,0.0003642982,0.0004025618,0.0004595008,0.0003675495,0.0005237302,0.0005585691,0.0003953782,0.000402714],"category_scores_gemma":[0.002875678,0.0002236849,0.0001646966,0.0008088258,0.001077401,0.001114318,0.0007523209,0.0006062638,0.00008234924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001046752,"about_ca_system_score_gemma":0.0008185975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002278513,"about_ca_topic_score_gemma":0.002203897,"domain_scores_codex":[0.999626,0.000116865,0.00001060412,0.00004263212,0.0001492811,0.00005458043],"domain_scores_gemma":[0.9986764,0.0008004605,0.0001850374,0.0001421795,0.0001594757,0.0000364476],"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":[0.00005195581,0.00001128422,0.0002762042,0.00002962372,0.0000111139,0.00005778477,0.0000633376,0.905153,0.005296736,0.06094783,0.0004679391,0.02763314],"study_design_scores_gemma":[0.00000799531,0.0000338436,0.0001068123,0.000006820643,0.000007565809,0.00004520054,0.00001509998,0.9636275,0.002517438,0.03247869,0.001142916,0.00001005201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05965743,0.0008937408,0.9364253,0.0002491916,0.0000281382,0.00002470545,0.00003529327,0.0002272311,0.002459112],"genre_scores_gemma":[0.8800203,0.001112501,0.1166648,0.00007316624,0.00005370592,0.00009755884,0.00005111345,0.00004481785,0.001882001],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002278513,"threshold_uncertainty_score":0.007594705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04456770545414097,"score_gpt":0.2658145010968959,"score_spread":0.2212467956427549,"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."}}