{"id":"W1966266694","doi":"10.1007/s11277-014-2013-7","title":"Min–Max Energy-Efficiency Analysis of Green Multiuser Wireless Systems","year":2014,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Fractional programming; Mathematical optimization; Energy (signal processing); Power (physics); Efficient energy use; Iterative method; Wireless; Convex optimization; Wireless network; Nonlinear programming; Parametric statistics; Scheme (mathematics); Parametric programming; Nonlinear system; Regular polygon; Algorithm; Telecommunications; Mathematics; Electrical engineering","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":[0.003013995,0.001992488,0.001487801,0.001030862,0.0005562633,0.002000849,0.00161144,0.001033644,0.006419906],"category_scores_gemma":[0.006679765,0.0007766019,0.0006618406,0.001614175,0.00169514,0.00209985,0.001841737,0.001125265,0.0006925681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002493965,"about_ca_system_score_gemma":0.001124243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001773104,"about_ca_topic_score_gemma":0.001559055,"domain_scores_codex":[0.998723,0.000662141,0.00002679873,0.000105411,0.0002487079,0.0002339755],"domain_scores_gemma":[0.9960426,0.003095983,0.0001712209,0.0001728191,0.0004108522,0.0001065652],"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":[0.0002190287,0.00006369316,0.0003583164,0.0001498545,0.00007126978,0.00006602273,0.00009348823,0.8755139,0.001974643,0.1060268,0.003071805,0.01239126],"study_design_scores_gemma":[0.000006640658,0.00002478081,0.0001807296,0.00001235779,0.00001030497,0.00002821982,0.00002580559,0.9660615,0.0003736334,0.03282225,0.0004454154,0.0000082125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0535881,0.002002191,0.9030018,0.001462055,0.0001208921,0.00009053929,0.0003796685,0.0002331224,0.03912163],"genre_scores_gemma":[0.9488246,0.001201109,0.0373062,0.0005320741,0.0001888612,0.0001235552,0.0001989797,0.0002131251,0.01141137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006419906,"threshold_uncertainty_score":0.02147669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01727128492941005,"score_gpt":0.2427634166427979,"score_spread":0.2254921317133879,"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."}}