{"id":"W2123958309","doi":"10.1109/iciinfs.2009.5429879","title":"Energy detection of primary signals over &amp;#x03B7; - &amp;#x03BC; fading channels","year":2009,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Fading; Detector; Energy (signal processing); Fading distribution; Channel (broadcasting); Cognitive radio; Maximal-ratio combining; Computer science; Electronic engineering; Detection theory; Telecommunications; Diversity scheme; SIGNAL (programming language); Statistics; Engineering; Mathematics; Wireless","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":[0.0002738719,0.0002061107,0.0003229105,0.0002298505,0.0001419357,0.0001320196,0.0003281688,0.00009796266,0.00005140473],"category_scores_gemma":[0.00002109419,0.0001922551,0.000150617,0.0006518384,0.00003494839,0.0004959771,0.00009307759,0.0001280715,0.00001401102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009211696,"about_ca_system_score_gemma":0.00003947105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001320293,"about_ca_topic_score_gemma":0.0001296488,"domain_scores_codex":[0.9983484,0.00008435675,0.0003530802,0.0004517414,0.000348494,0.0004139421],"domain_scores_gemma":[0.9990597,0.0001471238,0.0001493193,0.0004196237,0.0001106851,0.000113492],"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":[0.0000252831,0.000112678,0.00003833162,0.000009783392,0.00003847847,0.000007189096,0.0003960638,0.001518902,0.4116513,0.01585327,0.0005770238,0.5697716],"study_design_scores_gemma":[0.003012898,0.001309451,0.01763921,0.0005402785,0.0001069756,0.000458017,0.00004338707,0.3156243,0.4198469,0.1001389,0.1382335,0.003046177],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07468041,0.0003073493,0.9110457,0.0002705471,0.0003661038,0.00007869217,6.931755e-7,0.0001851288,0.01306543],"genre_scores_gemma":[0.985686,0.00007701143,0.0117414,0.001146376,0.0003133054,0.000001619302,0.000003832499,0.00001104249,0.001019381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9110056,"threshold_uncertainty_score":0.7839936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0206067857951036,"score_gpt":0.2369388735104645,"score_spread":0.2163320877153609,"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."}}