{"id":"W2052914062","doi":"10.1109/tap.2014.2367536","title":"Design of Near-Field Synthesis Arrays Through Global Optimization","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Antennas and Propagation","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Near and far field; Computer science; Field (mathematics); Antenna (radio); Relation (database); Set (abstract data type); Task (project management); Telecommunications; Mathematics; Physics; Engineering; Systems engineering; Optics; Data mining","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":[0.000518431,0.0007217072,0.0006061005,0.0004293967,0.0001919632,0.0006054663,0.0004425588,0.0006549993,0.001663401],"category_scores_gemma":[0.001180583,0.0003400129,0.0004176092,0.000348918,0.0006479597,0.0005111473,0.0006337065,0.0005400147,0.0005151972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003140099,"about_ca_system_score_gemma":0.000431016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003130423,"about_ca_topic_score_gemma":0.0004226664,"domain_scores_codex":[0.9997687,0.00007657504,0.000007697515,0.00004780925,0.00007588253,0.00002324614],"domain_scores_gemma":[0.9997286,0.0001376885,0.00004325838,0.00002804986,0.00004989171,0.00001248996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002982202,0.00002512905,0.0001921614,0.00007382247,0.00002377189,0.00003338176,0.00004976506,0.931461,0.01355309,0.01659753,0.0004782622,0.03748225],"study_design_scores_gemma":[0.00001814028,0.00007088451,0.00007037603,0.00001137085,0.000009572449,0.00002608511,0.00002049038,0.9859698,0.003659744,0.007802828,0.002333906,0.000006787429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008469077,0.00009812311,0.9875305,0.00006543924,0.00001462266,0.00002506764,0.00001677859,0.0001342893,0.003646098],"genre_scores_gemma":[0.3478132,0.0003743546,0.6467557,0.0001328634,0.00003662581,0.0003708825,0.0000991333,0.0001602911,0.004256968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001663401,"threshold_uncertainty_score":0.00556457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01364408647014764,"score_gpt":0.2098089686994788,"score_spread":0.1961648822293312,"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."}}