{"id":"W7042907016","doi":"","title":"Second-order cyclostationarity-based detection and
\\nclassification of LTE SC-FDMA signals for
\\ncognitive radio","year":2014,"lang":"en","type":"dissertation","venue":"Memorial University Research Repository (Memorial University)","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Memorial University of Newfoundland","keywords":"Cognitive radio; Detection theory; Autocorrelation; Channel (broadcasting); Telecommunications link; SIGNAL (programming language); Orthogonal frequency-division multiplexing; Term (time); Spectrum (functional analysis)","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001407902,0.0005157877,0.00084059,0.00227352,0.001928701,0.000316548,0.001230209,0.0007755668,0.00002223393],"category_scores_gemma":[0.0004297656,0.0006735402,0.000376757,0.002337009,0.0004473906,0.001054679,0.0002409276,0.001073835,0.000007823734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009503862,"about_ca_system_score_gemma":0.001651513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009923719,"about_ca_topic_score_gemma":0.003581142,"domain_scores_codex":[0.9943883,0.001638794,0.0004887409,0.001473998,0.001231742,0.0007784549],"domain_scores_gemma":[0.9924925,0.00191852,0.0007206383,0.000690128,0.003790224,0.000388016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.07667722,0.003378046,0.001466527,0.005588876,0.005053489,0.00338069,0.01558571,0.004575367,0.5245157,0.1304795,0.009924591,0.2193742],"study_design_scores_gemma":[0.04261527,0.008630614,0.01517677,0.002815825,0.002258653,0.0001105527,0.01616044,0.2313389,0.4718084,0.007717668,0.1946765,0.006690364],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6637747,0.0001435708,0.2626744,0.0002856662,0.01423654,0.003870407,0.0002112597,0.000414966,0.05438845],"genre_scores_gemma":[0.9803172,0.0001055302,0.00201268,0.00001372062,0.003125116,0.000002809697,0.0004323461,0.0000622505,0.01392835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3165425,"threshold_uncertainty_score":0.9995716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02195399445098365,"score_gpt":0.2575976299149957,"score_spread":0.235643635464012,"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."}}