{"id":"W2985074536","doi":"10.1049/iet-map.2019.0326","title":"Patch and monopole antennas in linear coprime arrays for direction of arrival estimation using compressed sensing","year":2019,"lang":"en","type":"article","venue":"IET Microwaves Antennas & Propagation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Deanship of Scientific Research, King Saud University","keywords":"Coprime integers; Direction of arrival; Multiple signal classification; Antenna (radio); Algorithm; Computer science; Mean squared error; Compressed sensing; Isotropy; Antenna array; Acoustics; Directional antenna; Mathematics; Electronic engineering; Telecommunications; Physics; Engineering; Optics; Statistics","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":[0.0004329925,0.0003743998,0.0003399386,0.0002953792,0.0001266964,0.0004665309,0.0003807534,0.0005245034,0.00175868],"category_scores_gemma":[0.001793966,0.0001976208,0.0003009433,0.0006590893,0.0004098967,0.0007663315,0.0004032089,0.000683209,0.0006172845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002055377,"about_ca_system_score_gemma":0.0002084215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000534474,"about_ca_topic_score_gemma":0.0006856939,"domain_scores_codex":[0.9996344,0.0001092088,0.00002166653,0.00008804763,0.0001224109,0.00002426041],"domain_scores_gemma":[0.999281,0.0003432233,0.0000853409,0.000150761,0.0001201626,0.00001951502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000608652,0.0001255477,0.0020688,0.0002947878,0.00009868243,0.0002876045,0.0002778818,0.1526297,0.2575128,0.02383331,0.003297674,0.5589646],"study_design_scores_gemma":[0.00004333806,0.0004468541,0.001936332,0.00004536111,0.00004754583,0.0004620848,0.0001013244,0.8757729,0.1035986,0.006342991,0.01115593,0.00004668641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04501307,0.000340277,0.9513495,0.0002004894,0.0001012256,0.00003411954,0.00006705219,0.0003844966,0.002509867],"genre_scores_gemma":[0.3950234,0.0005129815,0.6016482,0.0001989828,0.00009494762,0.00008005874,0.0001821327,0.00005903032,0.002200348],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00175868,"threshold_uncertainty_score":0.005883396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01634730045476682,"score_gpt":0.2720644922036911,"score_spread":0.2557171917489243,"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."}}