{"id":"W1986866934","doi":"10.1109/tsp.2014.2350966","title":"Synthesis of Linear and Planar Arrays With Minimum Element Selection","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; University of Victoria","keywords":"Beamwidth; Robustness (evolution); Planar array; Algorithm; Planar; Mathematics; Array gain; Amplitude; Iterative method; Computer science; Physics; Antenna array; Optics; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00008214408,0.0001076769,0.0001239858,0.0001075798,0.000110629,0.00001778031,0.00003165698,0.00004864809,0.00002072337],"category_scores_gemma":[0.000001100344,0.00009508645,0.00001891749,0.0001652849,0.00003007215,0.000130803,1.070728e-7,0.00009566513,0.000001687096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002003534,"about_ca_system_score_gemma":0.00001305583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003708996,"about_ca_topic_score_gemma":0.000008736297,"domain_scores_codex":[0.9994892,0.00001698079,0.0001457849,0.0001162787,0.0001162932,0.0001154698],"domain_scores_gemma":[0.9997907,0.00004670427,0.00003332565,0.00004325974,0.00004619028,0.00003985901],"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":[0.0001085932,0.00005505457,0.00003608167,0.0002309308,0.00004546243,5.05798e-7,0.0003088015,0.8297679,0.05554672,0.00001082588,0.00001353661,0.1138756],"study_design_scores_gemma":[0.0001700858,0.000114286,0.00002835479,0.0001290891,0.00004531912,0.000006187337,0.00007381301,0.7839655,0.2153197,0.00001075683,0.00003297665,0.0001039456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01664436,0.00002882888,0.9828142,0.00001640773,0.00002218465,0.00007634446,0.000002774752,0.0001147319,0.0002801701],"genre_scores_gemma":[0.9865628,0.00002206514,0.01330671,0.00001749117,0.00002533963,0.00001590755,7.26852e-7,0.00002376899,0.00002513454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9699185,"threshold_uncertainty_score":0.3877513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00855476399679188,"score_gpt":0.1971084902461968,"score_spread":0.1885537262494049,"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."}}