{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001250478,0.0001368067,0.0001204472,0.0001014031,0.0002345214,0.0000359022,0.00008495052,0.0000371024,0.00008616812],"category_scores_gemma":[0.000004224859,0.0001547363,0.0000362916,0.0001952351,0.00001572601,0.00008594053,0.0000700819,0.0001738971,0.000001670639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001747631,"about_ca_system_score_gemma":0.00003624862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005455311,"about_ca_topic_score_gemma":0.000006818534,"domain_scores_codex":[0.9991014,0.00004150529,0.0001833655,0.0001956581,0.0001540229,0.0003240205],"domain_scores_gemma":[0.9997492,0.00001552217,0.00003080086,0.0001398976,0.00002114454,0.00004345113],"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":[0.000009648111,0.00002902878,0.00002762523,0.00002896397,0.00004584893,0.000003654228,0.0005453025,0.6534093,0.3225209,0.0005877792,0.0002001574,0.02259174],"study_design_scores_gemma":[0.0002067532,0.00006315788,0.000003908182,0.000003638171,0.0000174374,0.00004749919,0.00003070411,0.9106116,0.07362689,0.0006585456,0.01452922,0.0002006787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3215683,0.01294373,0.6645779,0.00002759616,0.0001669816,0.00007403048,0.00000537742,0.000137325,0.0004988199],"genre_scores_gemma":[0.995268,0.001164344,0.003136629,0.0001802026,0.00004319845,0.00001064454,0.00003113124,0.00004525888,0.0001205809],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6736997,"threshold_uncertainty_score":0.6309962,"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."}}