{"id":"W2077647439","doi":"10.1109/icc.2013.6654748","title":"NBP: An efficient network-coding based backpressure algorithm","year":2013,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Linear network coding; Computer science; Network packet; Queue; Algorithm; Coding (social sciences); Scheduling (production processes); Computer network; Mathematical optimization; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003804273,0.0001429013,0.0001398118,0.00005584195,0.0003380173,0.0004082407,0.001253669,0.00004842412,0.0007769258],"category_scores_gemma":[0.00001441208,0.0001208242,0.00005109928,0.0004543144,0.0000341892,0.0004104732,0.0003913734,0.0001574927,0.0003037234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002816831,"about_ca_system_score_gemma":0.00004429443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001650168,"about_ca_topic_score_gemma":0.00001595103,"domain_scores_codex":[0.9986902,0.0002045135,0.0002092002,0.0003385413,0.0002111035,0.0003464022],"domain_scores_gemma":[0.9983804,0.0001348251,0.00005456509,0.001065783,0.0001954282,0.0001689865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001380003,0.000171181,0.0001903529,0.000004723919,0.00001669036,0.000002886891,0.000426663,0.07035388,0.0004895647,0.09512646,0.01796221,0.815254],"study_design_scores_gemma":[0.0002171126,0.00003569765,0.001212998,0.00001666508,0.000002003544,0.000001649743,0.00001381671,0.9873044,0.0002777884,0.0002094232,0.01052991,0.0001785198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001379984,0.0002435447,0.9850091,0.001490046,0.0002701231,0.0002472891,3.0783e-7,0.0003473681,0.01101224],"genre_scores_gemma":[0.6054753,0.00003929282,0.3913552,0.002217845,0.0001463465,0.00004666544,0.000005397398,0.00001063122,0.0007033485],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9169505,"threshold_uncertainty_score":0.8506793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02744633871262434,"score_gpt":0.2597783190792147,"score_spread":0.2323319803665904,"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."}}