{"id":"W2110997820","doi":"10.1109/ccece.2004.1345296","title":"FFT filter bank based majority and summation CFAR detectors: a comparative study","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Detector; Constant false alarm rate; Matched filter; Block (permutation group theory); Gaussian noise; Algorithm; Fast Fourier transform; Noise power; Additive white Gaussian noise; Noise (video); Computer science; Filter (signal processing); Mathematics; White noise; Telecommunications; Physics; Power (physics); Artificial intelligence","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":[0.00006880925,0.0001502743,0.0001590894,0.00007214912,0.0000424365,0.00002629064,0.00007096594,0.00003680486,0.00004862934],"category_scores_gemma":[0.000008885077,0.000141076,0.00001986143,0.00009792916,0.00002714968,0.0001968791,0.00002829611,0.0001080008,0.00001327167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009360843,"about_ca_system_score_gemma":0.000005708624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003672221,"about_ca_topic_score_gemma":0.0001258913,"domain_scores_codex":[0.9994375,0.00001870986,0.000142486,0.0001607677,0.00009752282,0.0001430045],"domain_scores_gemma":[0.9996994,0.00003449309,0.00001694742,0.0001733632,0.00003071696,0.00004507095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003919522,0.002133264,0.03138374,0.0007806931,0.000762501,0.0001915437,0.02297598,0.3474976,0.5645261,0.01238873,0.002289826,0.0146781],"study_design_scores_gemma":[0.004961397,0.001566669,0.1148351,0.0002232732,0.00007186808,0.00001284576,0.001795891,0.1436178,0.717554,0.01054176,0.003067242,0.001752203],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5858748,0.00001930892,0.4119059,0.00001169314,0.00003528622,0.0003333351,0.0000058584,0.0008578586,0.0009559585],"genre_scores_gemma":[0.9380473,0.000001928088,0.06181784,0.00001604322,0.00002375017,0.00005364059,0.000003860083,0.00001734984,0.00001832019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3521725,"threshold_uncertainty_score":0.5752914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02778102547973032,"score_gpt":0.264179479212706,"score_spread":0.2363984537329757,"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."}}