{"id":"W4294891534","doi":"10.1109/ojap.2022.3204927","title":"Wide-Angle Beam-Steering and Adaptive Impedance Matching With Reconfigurable Nonlocal Leaky-Wave Antenna","year":2022,"lang":"en","type":"article","venue":"IEEE Open Journal of Antennas and Propagation","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Leaky wave antenna; Antenna (radio); Varicap; Microstrip; Side lobe; Impedance matching; Computer science; Beam steering; Radiation pattern; Beam (structure); Aperiodic graph; Input impedance; Coupling (piping); Electrical impedance; Reconfigurable antenna; Electronic engineering; Acoustics; Optics; Capacitance; Materials science; Microstrip antenna; Physics; Antenna efficiency; Engineering; Telecommunications; Electrical engineering; Mathematics","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":[0.0005625476,0.0001597198,0.0002732317,0.0001094042,0.0002016039,0.0001514507,0.0001334095,0.00002957734,0.00002051339],"category_scores_gemma":[0.00001181404,0.0001355168,0.00003024997,0.0001358617,0.00003317086,0.0005132006,0.00003883664,0.0003584,6.828843e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005848307,"about_ca_system_score_gemma":0.00003599131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004218777,"about_ca_topic_score_gemma":0.00001178378,"domain_scores_codex":[0.9991314,0.00003378738,0.0003280763,0.0001425128,0.0001679707,0.0001962619],"domain_scores_gemma":[0.9995347,0.00005258828,0.0001396755,0.00008976617,0.0000910388,0.0000921937],"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":[0.0009788669,0.00008822053,0.0005874098,0.0004050219,0.0005147058,0.000571718,0.006999184,0.2037323,0.7378669,0.0004052796,0.001258751,0.04659158],"study_design_scores_gemma":[0.005098125,0.003820976,0.003228983,0.00202062,0.000235843,0.01171476,0.01161871,0.8540506,0.09996526,0.001027129,0.005561076,0.001657928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8617393,0.001676979,0.1351689,0.0001194729,0.0003538009,0.0002329508,0.00001235742,0.0000305178,0.0006657666],"genre_scores_gemma":[0.9968545,0.000288853,0.002531032,0.00003751281,0.0000761866,0.000007727099,0.000002120197,0.00003553592,0.0001665465],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6503183,"threshold_uncertainty_score":0.5526214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01756253071283471,"score_gpt":0.2102089350413588,"score_spread":0.192646404328524,"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."}}