{"id":"W1499282428","doi":"10.1109/icassp.2000.861086","title":"A filterbank structure for voice-band PCM channel pre-equalization","year":2002,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Intersymbol interference; Filter bank; Precoding; Channel (broadcasting); Bandlimiting; Nyquist ISI criterion; Transmitter; Computer science; Equalization (audio); Finite impulse response; Electronic engineering; Telecommunications; Algorithm; Engineering; Mathematics; MIMO","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":[0.0001185356,0.0001021463,0.00009773733,0.00008758646,0.0000902403,0.0001886505,0.0004125553,0.00008403672,0.0001047689],"category_scores_gemma":[0.00003913233,0.0000873755,0.00004282468,0.0002203513,0.00001359041,0.0005202285,0.00004543933,0.00005622359,0.00001584663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001698372,"about_ca_system_score_gemma":0.000009850963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009582129,"about_ca_topic_score_gemma":0.00002065143,"domain_scores_codex":[0.9992148,0.00003853584,0.0001679571,0.0002636445,0.000153285,0.0001617991],"domain_scores_gemma":[0.9993708,0.00005561681,0.0000701806,0.0003588603,0.00009776814,0.00004677842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001727042,0.0001880011,0.00009125562,0.00009309775,0.00004383237,0.000002219289,0.01657805,0.00124694,0.01508852,0.6905417,0.2491657,0.02694346],"study_design_scores_gemma":[0.000640903,0.0002759045,0.0002955591,0.00001938918,0.000007181477,0.00001259004,0.00001971237,0.7092312,0.1684409,0.06555092,0.05510601,0.0003997153],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003484818,0.0000427851,0.9908063,0.001681193,0.0001130635,0.0003908134,0.000007270947,0.0005398899,0.00293389],"genre_scores_gemma":[0.9153051,0.000008174576,0.07815028,0.002111731,0.00008532001,0.00005268911,0.00001266712,0.00001156226,0.004262508],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.912656,"threshold_uncertainty_score":0.3563069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0307945190345344,"score_gpt":0.2690713429683566,"score_spread":0.2382768239338222,"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."}}