{"id":"W4210354290","doi":"10.3390/electronics11030474","title":"Energy Efficiency and Throughput Maximization Using Millimeter Waves–Microwaves HetNets","year":2022,"lang":"en","type":"article","venue":"Electronics","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Throughput; Heterogeneous network; Mathematical optimization; Millimeter; Particle swarm optimization; Optimization problem; Efficient energy use; Maximization; Electronic engineering; Computer network; Algorithm; Engineering; Telecommunications; Wireless; Wireless network; Electrical engineering; Mathematics; Physics; Optics","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":[0.0004678082,0.0005998199,0.0005986876,0.0003559259,0.0003274347,0.0008225557,0.0003956689,0.0004582825,0.0006625642],"category_scores_gemma":[0.0006941308,0.0002014433,0.0004527582,0.0005367131,0.0004044867,0.0007175318,0.0006191484,0.0003403122,0.0001366244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005099117,"about_ca_system_score_gemma":0.0004020134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001012629,"about_ca_topic_score_gemma":0.001126144,"domain_scores_codex":[0.9997436,0.0001070644,0.000006685763,0.00004231686,0.00005322211,0.00004698523],"domain_scores_gemma":[0.9997227,0.000152166,0.00005354687,0.00002606336,0.00002936828,0.00001626733],"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":[0.00009377028,0.00005491424,0.0006362805,0.00005017673,0.00004308,0.00009518837,0.00003508658,0.9536976,0.008842675,0.01409092,0.000809026,0.0215513],"study_design_scores_gemma":[0.000006886429,0.00004239732,0.000210362,0.000003092575,0.000008210312,0.00002488147,0.00001344681,0.9938201,0.001732792,0.003552737,0.0005812974,0.000003742729],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1280737,0.0009558916,0.8574792,0.0003072901,0.00005453281,0.00004359804,0.00008165884,0.000296614,0.01270749],"genre_scores_gemma":[0.9468533,0.0005164574,0.04996418,0.00009406519,0.00003100266,0.00005764046,0.00006597379,0.00003313127,0.002384186],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001012629,"threshold_uncertainty_score":0.00369972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01359619285927947,"score_gpt":0.2092796176427072,"score_spread":0.1956834247834278,"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."}}