{"id":"W2154121411","doi":"10.1109/lawp.2009.2016442","title":"Highly Efficient Leaky-Wave Antenna Array Using a Power-Recycling Series Feeding Network","year":2009,"lang":"en","type":"article","venue":"IEEE Antennas and Wireless Propagation Letters","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Antenna array; Antenna (radio); Leaky wave antenna; Power (physics); Array gain; Series (stratigraphy); Dipole antenna; Computer science; Electronic engineering; Antenna efficiency; Radiation pattern; Acoustics; Electrical engineering; Physics; Microstrip antenna; Engineering; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002384838,0.0003391078,0.0004079842,0.000175109,0.0003293013,0.0001898621,0.00009823305,0.0001083694,0.00001006143],"category_scores_gemma":[0.00001110281,0.0003210319,0.000138523,0.0005448607,0.00009747112,0.0003237297,0.00001164362,0.0002597529,0.00001020464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007137463,"about_ca_system_score_gemma":0.00001707096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009772214,"about_ca_topic_score_gemma":0.000003636822,"domain_scores_codex":[0.9982712,0.00004794014,0.0004527276,0.0003910613,0.0002650617,0.0005719687],"domain_scores_gemma":[0.9994137,0.00003223924,0.0001132538,0.0002047324,0.00009945464,0.0001365937],"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":[0.00002623522,0.00001850474,0.0001551207,0.00003632633,0.00006508802,0.00007166005,0.0004290846,0.01547886,0.9823762,0.0001902663,0.0001411455,0.001011488],"study_design_scores_gemma":[0.0005288295,0.00007458622,0.001454321,0.000478015,0.0001214127,0.0001585221,0.0005070065,0.9683502,0.02728007,0.000146798,0.0001424817,0.0007577303],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6384477,0.0002785924,0.3592414,0.001194655,0.0003864216,0.0001212699,0.000003647967,0.0002502413,0.00007610147],"genre_scores_gemma":[0.9963438,0.000212619,0.001788047,0.001144445,0.0003954332,0.000004868547,0.000008811808,0.00004622319,0.00005576676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9550961,"threshold_uncertainty_score":0.9999242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01383309215407975,"score_gpt":0.2074406744465815,"score_spread":0.1936075822925017,"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."}}