{"id":"W2337787762","doi":"10.1177/1077546315621207","title":"An integrated multivariate empirical mode decomposition method towards modal identification of structures","year":2015,"lang":"en","type":"article","venue":"Journal of Vibration and Control","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Hilbert–Huang transform; Modal; Univariate; Computer science; Noise (video); Vibration; Multivariate statistics; Modal testing; Mode (computer interface); Modal analysis; Modal analysis using FEM; Identification (biology); Pattern recognition (psychology); Algorithm; Artificial intelligence; Energy (signal processing); Acoustics; Mathematics; Machine learning; Statistics; Physics; Materials science","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":[0.0003420211,0.0000789351,0.0001883591,0.0001232592,0.00002200666,0.00003532319,0.0000732245,0.00007797078,0.00000271941],"category_scores_gemma":[0.00005279679,0.00006267389,0.00003111202,0.00007248386,0.00001268833,0.0003709983,0.000003327486,0.0001376888,1.288786e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006700918,"about_ca_system_score_gemma":0.00004813092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003427913,"about_ca_topic_score_gemma":0.000002132455,"domain_scores_codex":[0.9991118,0.00011796,0.0004722342,0.00005824819,0.0001690159,0.00007072571],"domain_scores_gemma":[0.9992968,0.00003191284,0.00020151,0.00007454362,0.0002872254,0.0001080464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006049889,0.00003982632,0.001105661,0.00006628197,0.00009414819,0.00000343716,0.002023412,0.1067902,0.695165,0.0007985219,0.00021896,0.1930896],"study_design_scores_gemma":[0.001024805,0.000256837,0.06093853,0.00002167044,0.00003512664,0.00004081869,0.0001304612,0.8107595,0.1207883,0.005882996,0.00004058361,0.00008035015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.437888,0.00006195409,0.5616046,0.0001185963,0.000214934,0.00006519911,0.000006322426,0.00003482927,0.000005627755],"genre_scores_gemma":[0.9376297,0.00001073878,0.06217042,0.00003036015,0.0001429382,0.000002364159,0.000004293985,0.000008530007,6.737724e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7039694,"threshold_uncertainty_score":0.2555767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0327419652795124,"score_gpt":0.4263414947640699,"score_spread":0.3935995294845575,"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."}}