{"id":"W1996580322","doi":"10.1109/glocom.2014.7037436","title":"New asymptotics for performance of energy detector","year":2014,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Fading; Detector; Probability density function; Expression (computer science); Energy (signal processing); Maximal-ratio combining; Signal-to-noise ratio (imaging); Fading distribution; Algorithm; Representation (politics); Range (aeronautics); Asymptotic analysis; Computer science; Mathematics; Function (biology); Channel (broadcasting); Statistics; Telecommunications; Mathematical analysis; Rayleigh fading; Engineering","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":[0.004385669,0.001637336,0.001254523,0.00216492,0.000623445,0.002375619,0.002160024,0.001733973,0.003507098],"category_scores_gemma":[0.02901511,0.0005402726,0.0009961459,0.001827477,0.002499189,0.004528447,0.00278044,0.0031849,0.001268057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001970557,"about_ca_system_score_gemma":0.001099446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001048346,"about_ca_topic_score_gemma":0.0006655022,"domain_scores_codex":[0.9974073,0.0007166389,0.0001366785,0.000443664,0.001000909,0.0002947732],"domain_scores_gemma":[0.990837,0.005869378,0.0005890594,0.0009958377,0.001564223,0.00014451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008182443,0.00007039963,0.001370259,0.0003859217,0.0000623123,0.0002971965,0.0003408069,0.2693552,0.00917818,0.6612439,0.00411219,0.05350197],"study_design_scores_gemma":[0.00000827448,0.00004772746,0.0005068016,0.00009111877,0.00002355546,0.0003876614,0.00004743103,0.8388399,0.002257181,0.1543844,0.003365123,0.00004078995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009434051,0.002862208,0.9735461,0.0004720094,0.0001780245,0.00003059562,0.0001235065,0.0004380771,0.01291535],"genre_scores_gemma":[0.7670349,0.00860195,0.2071444,0.001350854,0.001100899,0.0003509104,0.0006793027,0.0005416959,0.01319511],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004385669,"threshold_uncertainty_score":0.0231939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008624191622398712,"score_gpt":0.2036107551740726,"score_spread":0.1949865635516739,"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."}}