{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001076182,0.0003969264,0.0002656172,0.0001403054,0.00007555106,0.0004100277,0.0005487478,0.0003720458,0.0006333354],"category_scores_gemma":[0.0001786203,0.000178585,0.0002800764,0.0002168478,0.0002369543,0.0004044385,0.0003530358,0.0002406491,0.0004662741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002088809,"about_ca_system_score_gemma":0.0001134257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007848937,"about_ca_topic_score_gemma":0.000161887,"domain_scores_codex":[0.9999002,0.00001846073,0.000005561576,0.0000303961,0.00002936554,0.00001594856],"domain_scores_gemma":[0.9998726,0.00002086967,0.00004989766,0.00003416121,0.00001320546,0.000009163063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001097879,0.0000457712,0.000698775,0.00006989319,0.00002922866,0.0001477333,0.00006079819,0.02591539,0.9395208,0.007229097,0.0004183814,0.02575443],"study_design_scores_gemma":[0.00008005725,0.0004346695,0.001165087,0.0000120947,0.00003621688,0.0004883455,0.0000396345,0.3692837,0.6189203,0.002210697,0.007280123,0.00004911428],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3709238,0.0003006018,0.6188319,0.0001789509,0.00005862469,0.00003940292,0.00008438744,0.0007380235,0.008844293],"genre_scores_gemma":[0.8520265,0.0001119663,0.1455262,0.00005705012,0.00001623188,0.00005289413,0.00005947501,0.00005855746,0.002091225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006333354,"threshold_uncertainty_score":0.002118707,"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."}}