{"id":"W4403936784","doi":"10.1109/twc.2024.3486023","title":"IRS Aided Millimeter-Wave Sensing and Communication: Beam Scanning, Beam Splitting, and Performance Analysis","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Photonic and Optical Devices","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Major Projects of Guangdong Education Department for Foundation Research and Applied Research; Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China; Alexander von Humboldt-Stiftung","keywords":"Extremely high frequency; Beam (structure); Millimeter; Telecommunications; Computer science; Optics; Physics","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":[0.001917018,0.001255621,0.0007594567,0.0007354394,0.0004110679,0.001012016,0.0007998244,0.0009529263,0.001299386],"category_scores_gemma":[0.003965987,0.000350714,0.0004837953,0.001273349,0.001151287,0.001366618,0.001127208,0.000934902,0.0004670268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001309979,"about_ca_system_score_gemma":0.001018866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003010691,"about_ca_topic_score_gemma":0.001576241,"domain_scores_codex":[0.9978406,0.0006551687,0.00006929725,0.0002085119,0.0009632236,0.0002630201],"domain_scores_gemma":[0.9970971,0.001398348,0.0004513035,0.0002827028,0.0007185951,0.00005185564],"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":[0.0003509738,0.0001670277,0.003540965,0.0004686861,0.0001175201,0.0002987525,0.0002304688,0.8232461,0.04844948,0.04837417,0.001796852,0.0729591],"study_design_scores_gemma":[0.000004155008,0.0001264906,0.0004450378,0.00001074967,0.00001518755,0.0001264238,0.00003368297,0.9922758,0.005187852,0.001365028,0.0003957246,0.00001386926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1032182,0.00422943,0.8747535,0.0005147626,0.00007620862,0.0001449499,0.000123633,0.0004372313,0.01650196],"genre_scores_gemma":[0.9497821,0.002324669,0.04548475,0.0001065576,0.00009588328,0.0001105345,0.00009830819,0.00003820413,0.00195894],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003010691,"threshold_uncertainty_score":0.01013827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02067424469810033,"score_gpt":0.2438344231564982,"score_spread":0.2231601784583979,"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."}}