{"id":"W2146054110","doi":"10.1109/cnsr.2009.13","title":"Carrier Frequency Offset Mitigation in OFDM Systems Using Efficient Tone Reservation","year":2009,"lang":"en","type":"article","venue":"","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Orthogonal frequency-division multiplexing; Carrier frequency offset; Fast Fourier transform; Orthogonality; Frequency offset; Computer science; Transmitter; Interference (communication); Reservation; Electronic engineering; Frequency-division multiplexing; Tone (literature); Algorithm; Reduction (mathematics); Offset (computer science); Telecommunications; Mathematics; Engineering; Computer network","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":[0.000165569,0.00009366276,0.0001096053,0.0001708384,0.00003305195,0.00003105546,0.00006394005,0.00007712651,0.0000339674],"category_scores_gemma":[0.00003857386,0.00009936168,0.00002129587,0.000374913,0.00001134975,0.0001516524,0.000004530521,0.00009933591,0.00001476381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003069103,"about_ca_system_score_gemma":0.00001618033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002149136,"about_ca_topic_score_gemma":0.00001870355,"domain_scores_codex":[0.9992147,0.00002616736,0.000283494,0.0001250787,0.0001804165,0.0001701258],"domain_scores_gemma":[0.9996955,0.00001198041,0.00002754845,0.0001710505,0.00005040037,0.00004348777],"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":[0.000001609719,0.00001361807,0.001115431,0.00002371352,0.000004334965,0.000002114999,0.0001845685,0.9062152,0.08887151,0.002839145,0.0005567531,0.0001720214],"study_design_scores_gemma":[0.0002201684,0.00001741904,0.01332543,0.0001109935,0.000005574883,0.00001334419,0.0002401568,0.9746847,0.01064359,0.0002567796,0.0002931638,0.0001887139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824572,0.0002211269,0.007964819,0.0001133036,0.0006881935,0.0002101535,0.000005420291,0.0002249833,0.008114801],"genre_scores_gemma":[0.9984222,0.000005625528,0.001289077,0.00001989179,0.0001101191,0.000007989371,0.000013296,0.00001203072,0.0001197764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07822792,"threshold_uncertainty_score":0.4051852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.019470539635121,"score_gpt":0.2700642429882785,"score_spread":0.2505937033531574,"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."}}