{"id":"W3109590391","doi":"10.1109/lwc.2020.3039483","title":"On the Aperture Efficiency of Intelligent Reflecting Surfaces","year":2020,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"East China Institute of Technology; Queen's University; Queen's University Belfast; Engineering and Physical Sciences Research Council; Leverhulme Trust; UK Research and Innovation","keywords":"Tapering; Aperture (computer memory); Computer science; Point (geometry); Antenna (radio); Antenna aperture; Work (physics); Electronic engineering; Telecommunications; Acoustics; Physics; Radiation pattern; Engineering; Computer graphics (images); Mathematics; Geometry; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001512341,0.0001811784,0.000209628,0.00007831648,0.0002445115,0.0000258113,0.002831212,0.00007365621,0.00001257471],"category_scores_gemma":[0.000233291,0.0001467838,0.00007716921,0.0006143252,0.0003910251,0.00009134644,0.0002480645,0.0006665974,0.00004547107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006090199,"about_ca_system_score_gemma":0.00001032016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007898327,"about_ca_topic_score_gemma":0.000008909346,"domain_scores_codex":[0.9989588,0.0001200165,0.0003851997,0.0001567876,0.0001810568,0.0001981072],"domain_scores_gemma":[0.9956787,0.001664304,0.0001223328,0.002443308,0.00005171429,0.00003970324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000109428,0.00007587559,0.0001525386,0.00006823056,0.00008837046,7.232213e-7,0.002712245,0.3546765,0.6018793,0.02678885,0.004008782,0.009537678],"study_design_scores_gemma":[0.000249433,0.00007894278,0.0001141351,0.0002164103,0.00001960888,0.00000305437,0.002451435,0.5964111,0.3855301,0.0006581755,0.01370512,0.0005624305],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6320511,0.001689282,0.2579412,0.1042774,0.0001342295,0.0005326422,0.00002411378,0.001608651,0.001741314],"genre_scores_gemma":[0.9913374,0.001213866,0.00522816,0.002091207,0.00001000794,0.00006735014,0.000009003117,0.00003913798,0.000003848628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3592863,"threshold_uncertainty_score":0.5985668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05931718062010783,"score_gpt":0.2828084682566031,"score_spread":0.2234912876364953,"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."}}