{"id":"W1982013992","doi":"10.4108/chinacom.2010.126","title":"A low complexity time domain spectrum sensing technique for OFDM","year":2010,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Orthogonal frequency-division multiplexing; Cognitive radio; Computer science; Fast Fourier transform; Time domain; Frequency domain; Simple (philosophy); Electronic engineering; Computational complexity theory; Spectrum (functional analysis); Telecommunications; Real-time computing; Algorithm; Wireless; Engineering; Channel (broadcasting); Physics","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":[0.0002108823,0.0003122858,0.0002787191,0.0002716589,0.0003132677,0.0003001473,0.0003219539,0.0004388451,0.001772187],"category_scores_gemma":[0.0009096282,0.0001247647,0.000225981,0.0003557186,0.0003178062,0.0005215744,0.000371215,0.0006624594,0.0005970468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001239174,"about_ca_system_score_gemma":0.0004026115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002745096,"about_ca_topic_score_gemma":0.0006075687,"domain_scores_codex":[0.9998,0.00003285245,0.000008562966,0.00003995808,0.000103237,0.000015343],"domain_scores_gemma":[0.9997311,0.0001084973,0.00003901034,0.00005623138,0.00005116011,0.00001401254],"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":[0.0002546185,0.0001172103,0.0003474767,0.0001712399,0.00002844314,0.000269173,0.0001073206,0.006181365,0.4775884,0.02379016,0.001774148,0.4893705],"study_design_scores_gemma":[0.000135167,0.001460697,0.002703269,0.00008087297,0.00007704047,0.005852912,0.00009566314,0.4895385,0.4304961,0.01251861,0.05694151,0.00009969464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01340689,0.0003648271,0.9829365,0.0001420662,0.0001388463,0.00005026278,0.00003478273,0.0002681936,0.002657618],"genre_scores_gemma":[0.2468264,0.0006450596,0.7449276,0.0002727724,0.0001915486,0.00008673609,0.00008602369,0.0000357609,0.006927981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001772187,"threshold_uncertainty_score":0.005928576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.013551063284077,"score_gpt":0.2400209471666497,"score_spread":0.2264698838825726,"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."}}