{"id":"W3090008919","doi":"10.1504/ijwmc.2020.10032469","title":"An enhanced multilevel ML-DFT codebook algorithm for hybrid beamforming of millimetre wave MIMO systems","year":2020,"lang":"en","type":"article","venue":"International Journal of Wireless and Mobile Computing","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Codebook; Computer science; Precoding; Baseband; Beamforming; MIMO; Algorithm; Electronic engineering; Transceiver; Base station; Wireless; Path loss; Telecommunications; Bandwidth (computing)","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":[0.0004674385,0.0005099382,0.0005775471,0.0004643646,0.0002289649,0.000606115,0.0009690639,0.0005640903,0.00315344],"category_scores_gemma":[0.001650761,0.000270434,0.0003675936,0.0006969739,0.0002734066,0.000760858,0.0009860529,0.000716014,0.001195812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003996494,"about_ca_system_score_gemma":0.0008712735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003050846,"about_ca_topic_score_gemma":0.004257814,"domain_scores_codex":[0.9996387,0.00007449085,0.00002312907,0.00004764823,0.0001765803,0.00003939696],"domain_scores_gemma":[0.9995676,0.0001774915,0.00004366819,0.00004861737,0.0001319769,0.00003071679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002649979,0.00007665646,0.0006328211,0.0001195273,0.00004469691,0.00008037337,0.0001074246,0.3285196,0.02719321,0.01861531,0.00250948,0.621836],"study_design_scores_gemma":[0.00001907932,0.00005751076,0.0001087195,0.00000598841,0.000004773134,0.00003974546,0.00001003505,0.9938959,0.002976323,0.001998613,0.0008755208,0.000007731064],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003770835,0.00008965906,0.9952363,0.00003684538,0.00001351681,0.00001798985,0.00002836801,0.0001678927,0.0006385492],"genre_scores_gemma":[0.2177504,0.0001943095,0.7783765,0.00009417492,0.00003870146,0.0001608267,0.0003149766,0.0000568624,0.003013276],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00315344,"threshold_uncertainty_score":0.01054931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01443991686888729,"score_gpt":0.2403519073041658,"score_spread":0.2259119904352785,"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."}}