{"id":"W2133845767","doi":"10.1109/wiopt.2011.5930037","title":"Joint routing, scheduling, and network coding for wireless multihop networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Linear network coding; Computer science; Maximum throughput scheduling; Unicast; Computer network; Scheduling (production processes); Wireless network; Signal-to-interference-plus-noise ratio; Distributed computing; Wireless mesh network; Wireless; Coding (social sciences); Throughput; Mathematical optimization; Dynamic priority scheduling; Round-robin scheduling; Multicast; Mathematics; Telecommunications; Quality of service","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006613823,0.0001544643,0.0002018292,0.00004099619,0.0004733058,0.0001541577,0.0005826498,0.0000682452,0.00002945796],"category_scores_gemma":[0.00004333675,0.0001391114,0.00005863855,0.0002503553,0.0000554026,0.000288223,0.0005972844,0.0001623864,0.000005077589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002051795,"about_ca_system_score_gemma":0.0000241968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009809629,"about_ca_topic_score_gemma":0.00005309983,"domain_scores_codex":[0.9988301,0.00008159103,0.0002800305,0.0003469542,0.00008139142,0.0003799297],"domain_scores_gemma":[0.9989474,0.0001509517,0.0001098512,0.0005378438,0.0001337322,0.0001201501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008598555,0.00003651327,0.001963665,0.00000686774,0.00002630796,0.000001158509,0.001248563,0.0007347747,0.0001100685,0.8641286,0.001334885,0.1304],"study_design_scores_gemma":[0.0003753977,0.00005010436,0.002019098,0.00005580931,0.000005293442,0.000004891824,0.00003596192,0.9946166,0.0002640703,0.0008810057,0.001480015,0.0002117804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004580552,0.0005223929,0.9889081,0.0002453069,0.0003106975,0.0002848064,2.022451e-7,0.0002370557,0.004910877],"genre_scores_gemma":[0.790926,0.0006252926,0.2073523,0.0006446978,0.0001381117,0.0000343346,0.000001614741,0.00001109827,0.0002664914],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9938818,"threshold_uncertainty_score":0.5672801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08204351785227845,"score_gpt":0.2750651369714942,"score_spread":0.1930216191192158,"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."}}