{"id":"W1648844940","doi":"10.1109/icc.1988.13696","title":"Adaptive identification of dispersive nonlinear data transmission channels","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Nonlinear system; Computer science; Intersymbol interference; Transmission (telecommunications); Identification (biology); Interference (communication); Algorithm; Data transmission; Electronic engineering; Telecommunications; Channel (broadcasting); Engineering; Physics; Computer network; Decoding methods","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":[0.0001081532,0.00009727643,0.0001135173,0.00005521919,0.00001872923,0.000005935772,0.000231814,0.00004301336,0.00005770428],"category_scores_gemma":[0.00002073638,0.00009227572,0.00002245336,0.0001172443,0.00002948806,0.0002719923,0.00002522324,0.00006948171,0.000009588214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002398761,"about_ca_system_score_gemma":0.00000672748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002848993,"about_ca_topic_score_gemma":7.760958e-7,"domain_scores_codex":[0.9994032,0.00001502394,0.0002032659,0.0001691262,0.00009700841,0.0001123173],"domain_scores_gemma":[0.9994411,0.00002394661,0.00003175531,0.0004259573,0.00004149165,0.00003572921],"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":[0.00002789744,0.0001075037,0.00003362304,0.0001414954,0.00009715223,0.000005516663,0.0006684362,0.03194287,0.9065546,0.01830512,0.001587246,0.04052848],"study_design_scores_gemma":[0.0001111042,0.00003238818,0.00005219611,0.0000375767,0.00001042511,0.000002559783,0.0001199463,0.1908777,0.7954214,0.001333734,0.01184804,0.0001529364],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003606248,0.0001223073,0.9925501,0.000009583934,0.00007594143,0.0001577782,0.0000555928,0.00030481,0.003117678],"genre_scores_gemma":[0.8117536,0.00009632397,0.1878402,0.000004249301,0.00001787329,0.000007091514,0.00004195781,0.00002489414,0.0002137622],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8081474,"threshold_uncertainty_score":0.3762895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03728367977414932,"score_gpt":0.2695151791760709,"score_spread":0.2322314994019216,"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."}}