{"id":"W2029565597","doi":"10.1109/glocom.2014.7037271","title":"Second-order statistic-based detection of Alamouti-coded OFDM signals for cognitive radio","year":2014,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Orthogonal frequency-division multiplexing; Cognitive radio; Computer science; Synchronization (alternating current); Algorithm; Modulation (music); Electronic engineering; Statistic; Signal-to-noise ratio (imaging); SIGNAL (programming language); Detection theory; Noise (video); WiMAX; Channel (broadcasting); Wireless; Telecommunications; Mathematics; Artificial intelligence; Engineering; Detector; Statistics","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":[0.0004289979,0.0001595843,0.0002787822,0.0001186889,0.0001223065,0.00007586413,0.0001770389,0.00006260307,0.00007867391],"category_scores_gemma":[0.0002402188,0.0001483086,0.00009509952,0.0003163038,0.00006685434,0.000170833,0.00003225751,0.0000863085,0.000007053963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002854102,"about_ca_system_score_gemma":0.00006694107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002533121,"about_ca_topic_score_gemma":0.0001903056,"domain_scores_codex":[0.9987076,0.0001197357,0.0002989037,0.0003806012,0.0001883974,0.0003047624],"domain_scores_gemma":[0.9977145,0.001417562,0.0001587882,0.0002039108,0.0004220916,0.0000832122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002990304,0.0002998711,0.0002883634,0.0001691232,0.0002072082,0.000007641371,0.0007054407,0.001828032,0.0832644,0.04905371,0.0007799861,0.8630972],"study_design_scores_gemma":[0.001335563,0.0003773955,0.001054399,0.00004092165,0.00002369772,0.000004693021,0.00002438095,0.8051426,0.1877905,0.003594888,0.000414229,0.0001966813],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02332293,0.0000326723,0.9733057,0.0001180171,0.0001984877,0.0003739652,0.00001776177,0.00009882097,0.002531647],"genre_scores_gemma":[0.9475402,0.000001476959,0.05171138,0.0004347325,0.00009491391,0.00001521082,0.00000878248,0.0000141584,0.0001791776],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9242172,"threshold_uncertainty_score":0.6047849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01317142223321068,"score_gpt":0.2438056860424239,"score_spread":0.2306342638092132,"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."}}