{"id":"W2029584533","doi":"10.1002/wcm.1050","title":"Power efficient scheduling over fading channel for cross‐layer optimization","year":2010,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Fading; Scheduling (production processes); Markov decision process; Computer network; Base station; Physical layer; Network packet; Queueing theory; Wireless; Mathematical optimization; Channel (broadcasting); Markov process; Telecommunications","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":[0.001378458,0.0009647502,0.0008423489,0.0003503382,0.0003177907,0.0009122473,0.0005494475,0.0005876133,0.002096722],"category_scores_gemma":[0.001822775,0.0003529235,0.0003559708,0.0006190337,0.0008098789,0.000778876,0.0007254377,0.0008037558,0.0002019732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001037328,"about_ca_system_score_gemma":0.001223118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003888469,"about_ca_topic_score_gemma":0.001571418,"domain_scores_codex":[0.9994923,0.0002385239,0.00001371796,0.00006919609,0.00008955417,0.00009671338],"domain_scores_gemma":[0.9991856,0.0005399106,0.0001122002,0.00003199813,0.00008819799,0.00004211703],"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":[0.00001909826,0.00001679269,0.00008433832,0.00002129509,0.00001369316,0.00002610841,0.00001087929,0.9909718,0.0009260889,0.004690676,0.000199982,0.003019155],"study_design_scores_gemma":[0.000003774601,0.00001449669,0.00003144947,0.000001335005,0.000003189497,0.000003192117,0.000003093974,0.9981878,0.0001674587,0.001509025,0.00007372981,0.000001397263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04898966,0.00046014,0.9467667,0.0002653308,0.00004461499,0.00003505266,0.00004000795,0.00009730694,0.003301185],"genre_scores_gemma":[0.9529267,0.0005005721,0.04384706,0.0001054905,0.00006439662,0.00008252037,0.00005129947,0.0000584286,0.002363523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003888469,"threshold_uncertainty_score":0.007731676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01176573105344811,"score_gpt":0.2741727705669365,"score_spread":0.2624070395134883,"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."}}