{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002626094,0.0006341696,0.0003215018,0.000297481,0.0002104446,0.0003832867,0.0004023446,0.0005978058,0.002133222],"category_scores_gemma":[0.0007841053,0.0002572089,0.0002758653,0.0005000426,0.0004140238,0.0006571559,0.000582767,0.0005564666,0.0008413887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003515153,"about_ca_system_score_gemma":0.0002469867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003679864,"about_ca_topic_score_gemma":0.0004468956,"domain_scores_codex":[0.9997912,0.00005544429,0.000007136341,0.00003900852,0.00009485386,0.00001231662],"domain_scores_gemma":[0.9997434,0.0001386973,0.00003137646,0.00002994585,0.00004558287,0.00001104998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003393719,0.00006131839,0.0004286484,0.0001798013,0.00006199814,0.0001420684,0.0001289444,0.1871279,0.3308157,0.04039919,0.002782389,0.4375326],"study_design_scores_gemma":[0.00003749097,0.0001761713,0.0003156643,0.00001977345,0.00001437013,0.0002695239,0.00001432566,0.923775,0.05716675,0.008168931,0.0100136,0.00002843255],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003403547,0.0001281716,0.9948657,0.00006222528,0.00002901437,0.00002275042,0.000009829595,0.0001808219,0.001297885],"genre_scores_gemma":[0.1348424,0.0005455181,0.8589793,0.0001380711,0.00009780032,0.0001491819,0.0000844333,0.00007171251,0.005091577],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002133222,"threshold_uncertainty_score":0.007136345,"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."}}