{"id":"W2094670259","doi":"10.1121/1.4778108","title":"A comparison of algorithms and the development of a new fast convergence and reduced computational load algorithm for multichannel active noise control","year":2002,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Algorithm; Convergence (economics); Computer science; Active noise control; Noise (video); Adaptive filter; Reduction (mathematics); Inverse; Filter (signal processing); Noise reduction; Mathematics; Artificial intelligence","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":[0.001793463,0.000807132,0.0007415405,0.0008596366,0.0004217554,0.0008543172,0.001423547,0.001100267,0.003863421],"category_scores_gemma":[0.005367286,0.000323258,0.0006169651,0.0006551601,0.0005592998,0.001716286,0.0006978748,0.001322734,0.0009613484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007353573,"about_ca_system_score_gemma":0.001111609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00194478,"about_ca_topic_score_gemma":0.001890939,"domain_scores_codex":[0.9988474,0.0002168891,0.000107802,0.0001979533,0.000562234,0.00006777088],"domain_scores_gemma":[0.9981406,0.000831865,0.0001114054,0.0002114236,0.0006577614,0.000046965],"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":[0.0002851269,0.0001242574,0.000450385,0.0002328969,0.00008311326,0.00005405849,0.0001458689,0.1712007,0.01374351,0.03925591,0.001848072,0.7725761],"study_design_scores_gemma":[0.00005934809,0.0001443739,0.00025829,0.00002545385,0.00001797815,0.0001200374,0.00002214022,0.9738681,0.01169492,0.005546153,0.00821535,0.00002781347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001698581,0.0001294179,0.9971477,0.0000343033,0.00005042832,0.00002428588,0.000004969057,0.000210978,0.0006991637],"genre_scores_gemma":[0.03860599,0.000275628,0.9585404,0.0000507637,0.00006894777,0.0001392233,0.00004978123,0.000119832,0.002149276],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003863421,"threshold_uncertainty_score":0.01292443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02337455500106959,"score_gpt":0.2784191411150752,"score_spread":0.2550445861140056,"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."}}