{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002502986,0.0001957346,0.0001976371,0.0001125652,0.0006435807,0.0001391337,0.0003585175,0.0001343169,0.00001039543],"category_scores_gemma":[0.00002587422,0.0002235185,0.0000546282,0.0002480131,0.0001130857,0.0001516524,0.0002293986,0.0003459795,0.000001558306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004008012,"about_ca_system_score_gemma":0.00001359767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000023186,"about_ca_topic_score_gemma":0.000003739974,"domain_scores_codex":[0.9989852,0.00002273386,0.000353077,0.000235463,0.00009117239,0.00031237],"domain_scores_gemma":[0.9986434,0.0002846335,0.0001006049,0.0007324426,0.0001552336,0.00008370771],"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":[0.000003355321,0.00003069962,0.0001520187,0.00002959906,0.00001588106,1.033191e-7,0.0005224058,0.9867321,0.002815745,0.001378191,0.000008324242,0.008311618],"study_design_scores_gemma":[0.0004341644,0.00001679092,0.0001120639,0.00006400242,0.000009620358,0.000004340687,0.0001076042,0.9975716,0.0004795621,0.00003330622,0.0009167848,0.0002502003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3658191,0.0004827717,0.6324088,0.00001514699,0.0003002814,0.0003867758,0.000006918112,0.0002856349,0.0002945333],"genre_scores_gemma":[0.8398508,0.0002402202,0.1595542,0.00002109642,0.00007930372,0.0001160391,0.00006542976,0.00006407782,0.000008868547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4740317,"threshold_uncertainty_score":0.9114822,"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."}}