{"id":"W1843104828","doi":"10.1002/wcm.2595","title":"Transmission scheduling in a multi‐channel wireless network with bidirectional relaying links","year":2015,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Linear network coding; Computer network; Relay; Maximum throughput scheduling; Scheduling (production processes); Network packet; Wireless network; Round-robin scheduling; Wireless; Fair-share scheduling; Quality of service; Mathematical optimization; Telecommunications","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":[0.001304465,0.000458689,0.0005234812,0.0003787043,0.0004846391,0.0006829447,0.0006075896,0.0005432982,0.0007572612],"category_scores_gemma":[0.002718115,0.0002972075,0.0002801303,0.0005854146,0.0006114402,0.0009098176,0.0005232547,0.0004790273,0.0001182244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001029065,"about_ca_system_score_gemma":0.0008097034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004096992,"about_ca_topic_score_gemma":0.003117722,"domain_scores_codex":[0.9993883,0.0002792309,0.00002225538,0.00008363494,0.0001031347,0.0001233771],"domain_scores_gemma":[0.9974558,0.001774034,0.0003876142,0.0001089959,0.0001995669,0.0000740856],"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":[0.00007823107,0.00003455365,0.0004902582,0.00004299529,0.00001651927,0.0001790686,0.00004886019,0.9790468,0.003464855,0.008572509,0.0002773342,0.007747988],"study_design_scores_gemma":[0.000003884554,0.00002310646,0.0001097621,0.000001901199,0.000005027926,0.00001714555,0.00001469453,0.9977876,0.0004285856,0.001492282,0.0001124796,0.000003619677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3995225,0.001205038,0.5934972,0.0003919555,0.00008936303,0.00007292506,0.00009429889,0.0001401166,0.004986602],"genre_scores_gemma":[0.9846339,0.0003184705,0.01409448,0.00002269868,0.00002055536,0.00002890004,0.00001850997,0.00001130758,0.0008512506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004096992,"threshold_uncertainty_score":0.008146286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06769034584289321,"score_gpt":0.3054646803065216,"score_spread":0.2377743344636284,"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."}}