{"id":"W2122506129","doi":"10.1109/vtcf.2006.422","title":"Decision Directed Iterative Equalization of OFDM Symbols Using Non-Uniform Interpolation","year":2006,"lang":"en","type":"article","venue":"IEEE Vehicular Technology Conference","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada; University of Ottawa","funders":"","keywords":"Interpolation (computer graphics); Orthogonal frequency-division multiplexing; Channel (broadcasting); Computer science; Fading; Equalization (audio); Algorithm; Linear interpolation; Electronic engineering; Mathematics; Telecommunications; Artificial intelligence; Pattern recognition (psychology); Engineering","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":[0.0005069951,0.0004109786,0.0004112963,0.0002904589,0.0002540217,0.0003537666,0.000614785,0.0003450844,0.0008200563],"category_scores_gemma":[0.002077638,0.0002121099,0.0002496911,0.0003394068,0.0003468019,0.0007104943,0.0004868105,0.0004630492,0.0002603132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002387968,"about_ca_system_score_gemma":0.0006232214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007237683,"about_ca_topic_score_gemma":0.001680609,"domain_scores_codex":[0.9994739,0.0001652308,0.00003949767,0.00007414528,0.0001901264,0.00005708542],"domain_scores_gemma":[0.9990616,0.0004901839,0.0001155373,0.0001395493,0.0001722899,0.00002077289],"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":[0.001038674,0.0002266494,0.00222884,0.0003342449,0.0001244616,0.0003633731,0.0003793286,0.1900057,0.1968454,0.01682849,0.00103031,0.5905944],"study_design_scores_gemma":[0.00006013137,0.0004308486,0.0010818,0.00002700344,0.00003507773,0.0004087187,0.0000308697,0.8723454,0.1197414,0.002640679,0.003157684,0.00004026195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03236374,0.0002135637,0.9660828,0.00004376207,0.00003531949,0.0000339466,0.00001926307,0.0002717066,0.0009359786],"genre_scores_gemma":[0.5263957,0.0002895734,0.4706158,0.00006856398,0.00003967573,0.00006025838,0.00009526776,0.00002887211,0.002406266],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0008200563,"threshold_uncertainty_score":0.002743423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01427669782840867,"score_gpt":0.2663668298369856,"score_spread":0.2520901320085769,"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."}}