{"id":"W7127324493","doi":"10.23919/isap63122.2025.11362222","title":"Adaptive Radar Cross Section Reduction via Active Nulling Using LCMV Beamforming","year":2025,"lang":"","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Radar cross-section; Reduction (mathematics); Beamforming; Adaptive beamformer; Radar; Clutter; Flexibility (engineering); Adaptive filter","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0005616104,0.0006156578,0.0006527237,0.0005573101,0.00133005,0.0005219022,0.0002134499,0.0005517781,0.0001037752],"category_scores_gemma":[0.00003723478,0.0006850539,0.0002702411,0.001271394,0.0001236437,0.00198987,0.00009066091,0.0008910013,0.00001779524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001687625,"about_ca_system_score_gemma":0.000270857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001645827,"about_ca_topic_score_gemma":0.00003049601,"domain_scores_codex":[0.9968147,0.000100744,0.001081049,0.0007751358,0.0004174022,0.0008109985],"domain_scores_gemma":[0.9988042,0.00007898789,0.0002880789,0.0003416398,0.0003392783,0.0001478644],"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":[0.0003025873,0.00007442073,0.00005649267,0.0009657187,0.000657767,0.00001303252,0.003138379,0.5899774,0.304616,0.0008154737,0.00008423529,0.09929845],"study_design_scores_gemma":[0.0007051432,0.00007546178,0.00008564337,0.001585968,0.000184574,0.000121572,0.005150904,0.8220804,0.1673546,0.0007773551,0.001183084,0.0006952263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2440915,0.001712988,0.7295595,0.0000244706,0.007195266,0.000488106,0.000006824635,0.0003006994,0.01662064],"genre_scores_gemma":[0.9795622,0.00005951569,0.0161613,0.00001886523,0.001618494,0.00001325564,0.000005868827,0.00009471072,0.002465777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7354708,"threshold_uncertainty_score":0.9999701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744249444299745,"score_gpt":0.2657232351555482,"score_spread":0.2482807407125508,"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."}}