{"id":"W2120062686","doi":"10.1109/aps.1994.407820","title":"Considerations for the hardware implementation of a four element digital beamformer","year":2002,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Adaptive beamformer; Computer science; Beamforming; Sampling (signal processing); Channel (broadcasting); Element (criminal law); Digital filter; Filter (signal processing); Computer hardware; Telecommunications; Computer vision","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":[0.0001361236,0.00005199776,0.00005580437,0.00003957625,0.000108282,0.0001752424,0.0001621313,0.0000145367,0.000270422],"category_scores_gemma":[0.00002827446,0.00003551145,0.00004926881,0.00008278488,0.00001688188,0.0005099153,0.00004742272,0.00002552092,0.000008401102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001209428,"about_ca_system_score_gemma":0.00001994527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000128403,"about_ca_topic_score_gemma":0.00004652382,"domain_scores_codex":[0.9994556,0.00001092684,0.0001998298,0.0001068102,0.0001340575,0.00009274615],"domain_scores_gemma":[0.9993539,0.0002182688,0.00007264993,0.0002200183,0.0001172147,0.00001789276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001212712,0.00007120729,0.0005103537,0.000008533014,0.00005169276,2.277974e-7,0.003967707,0.00009713635,0.0004148451,0.8088577,0.09105071,0.09496864],"study_design_scores_gemma":[0.002710983,0.001130344,0.003512346,0.00002037584,0.00005607542,0.00004662684,0.004191816,0.3372101,0.156466,0.1560548,0.3378533,0.0007472523],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006045818,0.00001519618,0.9888415,0.00727541,0.00003257675,0.0005016083,0.00001537297,0.00009591558,0.002617826],"genre_scores_gemma":[0.859574,0.000005758512,0.1388917,0.000921016,0.00001356743,0.0001215646,0.000002915859,0.000003271233,0.0004661525],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8589694,"threshold_uncertainty_score":0.2960932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.065215303563259,"score_gpt":0.3102025299997233,"score_spread":0.2449872264364643,"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."}}