{"id":"W2152923358","doi":"10.1109/vetec.1990.110294","title":"Acoustic noise suppression using regressive adaptive filtering","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Instituto de Telecomunicações","keywords":"Impulse noise; Active noise control; Noise (video); Microphone; Computer science; Adaptive filter; Colors of noise; Acoustics; Speech recognition; Gradient noise; Noise measurement; Noise floor; Filter (signal processing); Algorithm; Noise reduction; Loudspeaker; Physics; Artificial intelligence; Computer vision","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":[0.0003192127,0.0006910487,0.0004314616,0.0003832675,0.0001642365,0.0003480165,0.0005732815,0.0005087206,0.001769711],"category_scores_gemma":[0.0009880014,0.0001966784,0.0003712343,0.0003992356,0.0002434472,0.0003636941,0.0003684665,0.0004138239,0.001182255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000165957,"about_ca_system_score_gemma":0.0002711911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001804398,"about_ca_topic_score_gemma":0.001964205,"domain_scores_codex":[0.9996643,0.00005851366,0.0000178156,0.00007078317,0.0001620874,0.00002660423],"domain_scores_gemma":[0.9996411,0.0001443098,0.00004138465,0.00003915344,0.0001229475,0.00001117933],"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":[0.0004170158,0.0001596503,0.0005070095,0.0001813625,0.00005518717,0.0001412277,0.000116186,0.05173111,0.5596049,0.003006676,0.0009635813,0.3831161],"study_design_scores_gemma":[0.00005867072,0.0004319695,0.001624914,0.00003023401,0.00007470412,0.0002681017,0.00002688192,0.7352492,0.2509702,0.00139402,0.009831403,0.00003970208],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04269402,0.0002717358,0.9520013,0.000061866,0.00005732228,0.00003721071,0.00003900556,0.001603972,0.003233556],"genre_scores_gemma":[0.4314633,0.0005612132,0.5569651,0.00009376424,0.00006173306,0.0001070452,0.0002562867,0.0002228386,0.01026882],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001804398,"threshold_uncertainty_score":0.005920291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04371669583990384,"score_gpt":0.2473298531274677,"score_spread":0.2036131572875638,"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."}}