{"id":"W2037153888","doi":"10.1109/surv.2013.042313.00226","title":"A Survey of Energy Efficient Resource Management Techniques for Multicell Cellular Networks","year":2013,"lang":"en","type":"article","venue":"IEEE Communications Surveys & Tutorials","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":151,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Radio resource management; Cellular network; Resource management (computing); Context (archaeology); Efficient energy use; Stochastic geometry; Resource allocation; Resource (disambiguation); Computer network; Distributed computing; Process (computing); Key (lock); Heterogeneous network; Telecommunications; Wireless network; Wireless; Engineering; Computer security","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":[0.002878732,0.000210644,0.0003760872,0.0001593731,0.0001313021,0.00004222945,0.0008698154,0.0001448884,0.00001015735],"category_scores_gemma":[0.0001310356,0.0002307975,0.00007537914,0.0004473335,0.00009785654,0.0001018864,0.0001332448,0.00009978685,0.000007984765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001206903,"about_ca_system_score_gemma":0.00001247523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008271207,"about_ca_topic_score_gemma":0.000172365,"domain_scores_codex":[0.9974549,0.001164175,0.0007663205,0.0002026051,0.0001356018,0.0002763622],"domain_scores_gemma":[0.9958221,0.001403795,0.0002183568,0.002021393,0.0004680166,0.00006631909],"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":[0.000005520398,0.0001127888,0.0001008251,0.00009803552,0.00009641563,1.238268e-7,0.00009302991,0.9840918,0.005185886,0.0007735536,0.002542587,0.006899472],"study_design_scores_gemma":[0.0005306777,0.00003741477,0.0009658625,0.000123483,0.00004982195,3.22836e-7,0.00006954125,0.9516553,0.02213261,0.0000563648,0.02393585,0.0004427682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001279218,0.001338858,0.9927719,0.00001068525,0.0007234531,0.001264625,0.00006402926,0.0003698769,0.002177303],"genre_scores_gemma":[0.9511408,0.0003967849,0.0464736,0.000007975109,0.0001240215,0.001076471,0.0004160399,0.00008202404,0.0002822963],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9498616,"threshold_uncertainty_score":0.9411647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02729309781592509,"score_gpt":0.258294872438498,"score_spread":0.2310017746225729,"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."}}