{"id":"W2042909471","doi":"10.1109/camsap.2013.6714087","title":"Frequency domain distributed OFDM source detection","year":2013,"lang":"en","type":"article","venue":"","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Detector; Orthogonal frequency-division multiplexing; Computer science; Frequency domain; Noise (video); Algorithm; Multiplexing; Time domain; Noise power; Signal-to-noise ratio (imaging); Computational complexity theory; Power (physics); Electronic engineering; Telecommunications; Artificial intelligence; Engineering; Physics; Channel (broadcasting)","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":[0.0005917493,0.0006159082,0.0005771511,0.0002779742,0.0002572178,0.0005571632,0.0009534227,0.0009328933,0.0009478796],"category_scores_gemma":[0.002146084,0.0001744284,0.0004557337,0.0004527339,0.0007463156,0.0009385706,0.0006260233,0.0005262194,0.0001813064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004781024,"about_ca_system_score_gemma":0.0004440708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009332458,"about_ca_topic_score_gemma":0.000754841,"domain_scores_codex":[0.9994736,0.0001908223,0.00001137741,0.0001260932,0.0001437759,0.00005435038],"domain_scores_gemma":[0.9991394,0.0005703025,0.00009325702,0.00007694551,0.0001004141,0.00001963182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001088718,0.00008745157,0.001287793,0.0001267081,0.00006242858,0.0005337499,0.00007776509,0.8722387,0.01092611,0.07445697,0.00095957,0.0391339],"study_design_scores_gemma":[0.00001033516,0.00004809345,0.0001441313,0.000003629521,0.000009877621,0.0001130438,0.00001449286,0.988792,0.001648794,0.008761714,0.000446818,0.000006942004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02990689,0.0003342574,0.9666578,0.000213046,0.00004729358,0.00002838991,0.00004196245,0.00008118017,0.002689284],"genre_scores_gemma":[0.8875593,0.0005842631,0.1091696,0.00009211322,0.0001165662,0.00005667457,0.00005229806,0.00001146705,0.002357689],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009534227,"threshold_uncertainty_score":0.003468931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005481812934194223,"score_gpt":0.1880747288448169,"score_spread":0.1825929159106227,"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."}}