{"id":"W2980169183","doi":"10.1109/tcomm.2019.2946814","title":"Generalized FFT-Based One-Bit Quantization System for Wideband Spectrum Sensing","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Quantization (signal processing); Fast Fourier transform; Computer science; Wideband; Electronic engineering; Asynchronous communication; False alarm; Algorithm; Telecommunications; Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002527524,0.0001975919,0.0002739369,0.0002559423,0.0007702897,0.000233102,0.0007552268,0.00009463508,0.00001073333],"category_scores_gemma":[0.000005580027,0.0002191547,0.0001980857,0.0006302657,0.00006183321,0.0002905125,0.000007200673,0.0002525781,0.000065861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002063968,"about_ca_system_score_gemma":0.0001193275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001013658,"about_ca_topic_score_gemma":0.0003870979,"domain_scores_codex":[0.9984671,0.0002225015,0.0003718303,0.0003965683,0.0002196786,0.0003222646],"domain_scores_gemma":[0.9968549,0.0006881531,0.0001476318,0.002049729,0.0001692958,0.00009027943],"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":[0.000487839,0.002200339,0.0001395472,0.000497799,0.0008903706,0.00001251545,0.002574632,0.3238515,0.09977714,0.3658215,0.000638426,0.2031085],"study_design_scores_gemma":[0.001087748,0.0001140315,0.00003620462,0.0001911701,0.00005323854,0.00001786692,0.00005509689,0.9748868,0.02146306,0.0005656666,0.00125136,0.0002777458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004990896,0.00009908388,0.987251,0.004491167,0.0006949704,0.0007795878,0.00002091209,0.0004192936,0.001253103],"genre_scores_gemma":[0.8885179,0.00005602132,0.1109099,0.0002256217,0.00003963495,0.00002518789,0.00001797543,0.00002899886,0.0001787121],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.883527,"threshold_uncertainty_score":0.8936867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03478331288619931,"score_gpt":0.2630398579170746,"score_spread":0.2282565450308753,"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."}}