{"id":"W1963864898","doi":"10.1016/j.sigpro.2004.05.008","title":"A method of extraction of nonstationary sinusoids","year":2004,"lang":"en","type":"article","venue":"Signal Processing","topic":"Control Systems and Identification","field":"Engineering","cited_by":115,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Robustness (evolution); Nonlinear system; Uniqueness; Mathematical proof; Algorithm; Amplitude; Differential equation; Noise immunity; Software; Noise (video); Signal processing; Computer science; Control theory (sociology); Nonlinear dynamical systems; Mathematics; Mathematical analysis; Digital signal processing; Artificial intelligence; Physics","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":[0.0001448494,0.00004590695,0.00009622507,0.00006998307,0.00002135418,0.000008977465,0.00003390093,0.00003025585,0.00001224177],"category_scores_gemma":[0.000005538838,0.00004703163,0.00002751032,0.0001368232,0.00001155326,0.0001930965,0.000002733996,0.0000408765,0.000002240131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002935937,"about_ca_system_score_gemma":0.00003473164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003904013,"about_ca_topic_score_gemma":0.000004675091,"domain_scores_codex":[0.9995447,0.000009300737,0.0002243573,0.00005948335,0.000105849,0.00005628704],"domain_scores_gemma":[0.9997613,0.00001893517,0.00007614587,0.00004415273,0.0000853358,0.00001416411],"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":[0.000006129446,0.00001677229,0.00003970419,0.0002735387,0.000008814125,4.116266e-7,0.000346108,0.0736366,0.7878339,0.0002143392,0.000009675524,0.137614],"study_design_scores_gemma":[0.001306181,0.00008187861,0.009806528,0.0008137188,0.00007663531,0.00005051224,0.0008750512,0.2688972,0.7087774,0.008425023,0.0005838393,0.0003059804],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07355444,0.0006564586,0.9239755,0.00001582021,0.00004496978,0.00007192385,0.000002902249,0.00004391358,0.00163413],"genre_scores_gemma":[0.9839227,0.000002842795,0.0159979,0.000001701818,0.0000356809,0.000005200847,0.000003527321,0.000008533419,0.00002189468],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9103683,"threshold_uncertainty_score":0.1917894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01062568655568175,"score_gpt":0.2664970338967838,"score_spread":0.2558713473411021,"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."}}