{"id":"W2593567713","doi":"","title":"Adaptive microwave beamforming using fast perturbation","year":2006,"lang":"en","type":"article","venue":"International Symposium on Antenna Technology and Applied Electromagnetics","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Beamforming; Adaptive beamformer; Converters; Computer science; Electronic engineering; Microwave; Weighting; Perturbation (astronomy); Electrical engineering; Engineering; Telecommunications; Acoustics; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.00004268116,0.0001950202,0.000141085,0.000310468,0.0001004332,0.00003889314,0.0001459818,0.0002166506,0.00001110723],"category_scores_gemma":[0.00000374933,0.0002042681,0.00002963381,0.0002777393,0.0001176223,0.00006795782,0.00002728784,0.0002323684,0.00001281089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009821304,"about_ca_system_score_gemma":0.000008020362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000363491,"about_ca_topic_score_gemma":0.00000481381,"domain_scores_codex":[0.9991613,0.000004841566,0.000222581,0.0002255689,0.0001280244,0.0002576562],"domain_scores_gemma":[0.9997346,0.00002067597,0.00005148166,0.0001052085,0.00006135061,0.00002665672],"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":[0.00003902427,0.00003662188,0.00008338577,0.000005273448,0.00002897013,0.000003903102,0.00002644402,0.006807914,0.8699103,0.1205478,0.00005589107,0.002454399],"study_design_scores_gemma":[0.0006898337,0.0002785164,0.0002424645,0.00004214445,0.00003574495,0.0001145996,0.000118717,0.855745,0.1250249,0.01664485,0.0006332587,0.0004299188],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4258556,0.0003899799,0.5373549,0.0008947189,0.0003323358,0.0003547307,0.00001490811,0.0008633765,0.03393938],"genre_scores_gemma":[0.9874408,0.0001612532,0.01174947,0.00009485849,0.0001074669,0.00001762683,0.00003321263,0.00003334072,0.0003619907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8489371,"threshold_uncertainty_score":0.8329811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004721358501947866,"score_gpt":0.1829472142594309,"score_spread":0.1782258557574831,"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."}}