{"id":"W4387204296","doi":"10.1061/ajrua6.rueng-1082","title":"Application of Dual-Tree Complex Wavelet Packet Transform for Generating Synthetic Multivariate Nonstationary Non-Gaussian Thunderstorm Wind Records","year":2023,"lang":"en","type":"article","venue":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A Civil Engineering","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Multivariate statistics; Computer science; Wavelet; Network packet; Gaussian; Dual (grammatical number); Pattern recognition (psychology); Algorithm; Artificial intelligence; Speech recognition; Data mining; Machine learning; Physics; Computer network","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":[0.0004827517,0.0003345368,0.0002113031,0.0004952474,0.0001344231,0.0003198954,0.0003609467,0.0003414641,0.0004070008],"category_scores_gemma":[0.001837757,0.0001360467,0.0003013334,0.0007222273,0.0001529572,0.0004092579,0.0003601766,0.0004219949,0.0001316701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000157339,"about_ca_system_score_gemma":0.0004444481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001398989,"about_ca_topic_score_gemma":0.00131123,"domain_scores_codex":[0.9998579,0.00002443408,0.000008129805,0.00002744728,0.00007081342,0.00001129668],"domain_scores_gemma":[0.999584,0.0001730336,0.00003628548,0.00005257354,0.0001379699,0.00001599799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002810449,0.0001824347,0.005992517,0.0001462908,0.00006660819,0.0003555848,0.0001319299,0.5016443,0.08657962,0.009977373,0.001552075,0.3930902],"study_design_scores_gemma":[0.000005603078,0.00001876892,0.0006577242,0.000001385962,0.000004315941,0.00003207184,0.00000493683,0.9907137,0.007854994,0.0003900417,0.0003119645,0.000004499418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08846024,0.00005049516,0.910262,0.00006043008,0.00002599677,0.00003637918,0.00009149197,0.0002118882,0.0008011019],"genre_scores_gemma":[0.4822741,0.0001468856,0.5164886,0.00002448548,0.0000128702,0.00004943845,0.0003656702,0.00005674989,0.0005812848],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001398989,"threshold_uncertainty_score":0.002781689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01642679463965812,"score_gpt":0.2509519272398883,"score_spread":0.2345251326002302,"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."}}