{"id":"W3139045596","doi":"10.3390/s21062076","title":"Optimal Access Point Power Management for Green IEEE 802.11 Networks","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Mathematical optimization; Key (lock); Nonlinear programming; Software deployment; Decomposition; Integer programming; Transmission (telecommunications); Power (physics); Point (geometry); Nonlinear system; Distributed computing; Computer network; Algorithm; Telecommunications; Mathematics","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":[0.000245071,0.0001762065,0.0002027746,0.00004977201,0.0001422579,0.0003458002,0.000834567,0.00008642833,0.00005051072],"category_scores_gemma":[0.000005193284,0.0001664356,0.0001407312,0.0003715399,0.00002596735,0.0002811795,0.0004135713,0.0001144672,0.00001960042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002977223,"about_ca_system_score_gemma":0.00002658453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001909371,"about_ca_topic_score_gemma":0.0000235317,"domain_scores_codex":[0.9984817,0.00006808562,0.0002395271,0.0005181,0.0002103084,0.0004822972],"domain_scores_gemma":[0.9989259,0.00008832078,0.00008160724,0.000673502,0.0001108607,0.0001198024],"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":[0.0000662717,0.0001794388,0.0007320173,0.0001124419,0.0001751185,0.0005992794,0.0004441119,0.8385375,0.00002708346,0.04115867,0.0449603,0.07300778],"study_design_scores_gemma":[0.001124476,0.0001211566,0.00247502,0.000123946,0.00002141653,0.00004040979,0.00006132069,0.8832705,0.00130794,0.001716412,0.1091759,0.0005614864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03487022,0.00009537634,0.9502096,0.002435739,0.001302907,0.004712543,0.000006009111,0.0002482551,0.006119315],"genre_scores_gemma":[0.7398648,0.00009248669,0.2299812,0.005093769,0.00176693,0.005489746,0.00003107667,0.0001286549,0.0175514],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7202285,"threshold_uncertainty_score":0.6787045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02285820381752215,"score_gpt":0.2862406702470449,"score_spread":0.2633824664295228,"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."}}