{"id":"W2150919096","doi":"10.1109/twc.2011.021611.101864","title":"QoS, Channel and Energy-Aware Packet Scheduling over Multiple Channels","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Network packet; Quality of service; Scheduling (production processes); Computer network; Robustness (evolution); Efficient energy use; Channel (broadcasting); Link adaptation; Distributed computing; Fading; Mathematical optimization","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":[0.0008659583,0.0005941559,0.0006021423,0.0003549129,0.0005201386,0.0009465398,0.0006850427,0.0004136706,0.00134768],"category_scores_gemma":[0.003162219,0.0002941428,0.0002266767,0.0007260314,0.0005045122,0.001366989,0.0007024947,0.0007884319,0.0002187529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007249633,"about_ca_system_score_gemma":0.0009068798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001204205,"about_ca_topic_score_gemma":0.001655907,"domain_scores_codex":[0.9993874,0.0001801945,0.00002720052,0.00008127285,0.0002000139,0.0001239914],"domain_scores_gemma":[0.9982185,0.00102003,0.0001780363,0.0002185282,0.0002677696,0.0000972255],"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":[0.0003524914,0.00008354753,0.0007948351,0.0001327549,0.00003856398,0.0001712691,0.00005027461,0.8650599,0.0177644,0.05141245,0.001716165,0.06242343],"study_design_scores_gemma":[0.000008839253,0.00004214427,0.0001924586,0.000003998201,0.00001020581,0.00005421028,0.00001760065,0.9870476,0.002629581,0.009124788,0.0008613155,0.000007352885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09829481,0.00177258,0.8903105,0.0006702343,0.0003216706,0.00006345424,0.0001004344,0.000235021,0.008231323],"genre_scores_gemma":[0.9463598,0.0006446391,0.05001456,0.00006982159,0.0001407138,0.00003596126,0.000051361,0.00004660693,0.002636604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00134768,"threshold_uncertainty_score":0.005259931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03106764346363201,"score_gpt":0.2322690933870598,"score_spread":0.2012014499234278,"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."}}