{"id":"W1791228942","doi":"10.1007/978-94-007-1703-9_3","title":"Short-Time Autoregressive (STAR) Modeling for Operational Modal Analysis of Non-stationary Vibration","year":2011,"lang":"en","type":"book-chapter","venue":"","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hydro-Québec; Polytechnique Montréal; École de Technologie Supérieure","funders":"","keywords":"Autoregressive model; Vibration; Short-time Fourier transform; Modal; STAR model; Modal analysis; Operational Modal Analysis; Autoregressive–moving-average model; Noise (video); Mathematics; Fourier transform; Computer science; Algorithm; Control theory (sociology); Fourier analysis; Time series; Mathematical analysis; Acoustics; Statistics; Physics; Autoregressive integrated moving average; 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":[0.0005549269,0.0009772149,0.0006603978,0.0003173835,0.0001728279,0.0006470475,0.0008793746,0.0006530748,0.005146096],"category_scores_gemma":[0.0008768368,0.0003929572,0.0008066134,0.0009262454,0.0003573748,0.0009423749,0.0003618551,0.001476041,0.004380105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002184194,"about_ca_system_score_gemma":0.0003028007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001333026,"about_ca_topic_score_gemma":0.002470205,"domain_scores_codex":[0.9996724,0.00008328949,0.00002315929,0.00006875044,0.0001399758,0.00001242615],"domain_scores_gemma":[0.9996696,0.000184487,0.00002500933,0.00005037441,0.00006449502,0.000006071051],"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":[0.00006092866,0.00007868424,0.0003203056,0.000590589,0.0001508987,0.0001154975,0.0001532535,0.1503964,0.02662485,0.1141117,0.03071987,0.676677],"study_design_scores_gemma":[0.00000696438,0.00007249089,0.0006171705,0.00006842503,0.00005613351,0.0001882077,0.00002802641,0.8487825,0.006816293,0.07369353,0.06962407,0.0000462221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004309109,0.001488461,0.9958463,0.00004923772,0.0001173002,0.000006696844,0.00005787077,0.0004158911,0.001587395],"genre_scores_gemma":[0.06045657,0.01060086,0.8915913,0.0002673507,0.000580509,0.000152072,0.001194734,0.0008228502,0.03433377],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005146096,"threshold_uncertainty_score":0.01721537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03465061207251673,"score_gpt":0.283059476310852,"score_spread":0.2484088642383353,"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."}}