{"id":"W2075565834","doi":"10.1016/j.sigpro.2012.02.019","title":"A generalized synchrosqueezing transform for enhancing signal time–frequency representation","year":2012,"lang":"en","type":"article","venue":"Signal Processing","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":218,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Instantaneous phase; Wavelet; Time–frequency analysis; SIGNAL (programming language); Time–frequency representation; Mathematics; Dimension (graph theory); Wavelet transform; Algorithm; Continuous wavelet transform; Computer science; Artificial intelligence; Discrete wavelet transform; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002690938,0.0005587984,0.0002831006,0.0003823584,0.0001572624,0.000461949,0.0003261903,0.0004057875,0.003593399],"category_scores_gemma":[0.000776105,0.0001310565,0.0002842002,0.0006263631,0.0002677163,0.000785533,0.0004487057,0.0004663845,0.001159389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000128635,"about_ca_system_score_gemma":0.0002624682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004267488,"about_ca_topic_score_gemma":0.0007223113,"domain_scores_codex":[0.9998115,0.00004564588,0.00001108295,0.0000330016,0.00008798062,0.00001089772],"domain_scores_gemma":[0.999787,0.00006069151,0.00002091125,0.00005076313,0.00006903324,0.00001166644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003025272,0.00007453175,0.0003619341,0.0002494027,0.00004173817,0.0002313145,0.0001143878,0.02944084,0.394531,0.047165,0.00303579,0.5244515],"study_design_scores_gemma":[0.00004085658,0.0002910315,0.001056005,0.0000328747,0.00006806641,0.0008667252,0.00005072657,0.8180577,0.1336602,0.01482211,0.0310155,0.00003832009],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006843304,0.0001065315,0.9914301,0.00006910427,0.00004908566,0.00001819137,0.00004325037,0.0002534386,0.00118704],"genre_scores_gemma":[0.1899366,0.0006084152,0.8006912,0.0001568646,0.0001641074,0.00006194547,0.0003990693,0.000194486,0.007787376],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003593399,"threshold_uncertainty_score":0.01202106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01503089468195925,"score_gpt":0.2967754132005522,"score_spread":0.2817445185185929,"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."}}