{"id":"W3177837582","doi":"10.1016/j.ymssp.2021.108166","title":"Substructural damage detection using frequency response function based inverse dynamic substructuring","year":2021,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Substructure; Frequency response; Residual; Decoupling (probability); Response analysis; Structural engineering; Finite element method; Engineering; Inverse; Control theory (sociology); Computer science; Algorithm; Mathematics; Control engineering","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":[0.0001832292,0.0004706772,0.0003801968,0.001083536,0.0001546193,0.0003823998,0.0004275159,0.000709804,0.001311163],"category_scores_gemma":[0.0007310023,0.0001891663,0.0002719222,0.000522733,0.0002679522,0.0006686734,0.0003354322,0.0003566206,0.0006045907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001536819,"about_ca_system_score_gemma":0.0001486189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006584526,"about_ca_topic_score_gemma":0.001118789,"domain_scores_codex":[0.9998156,0.00001735729,0.00000846353,0.00004542183,0.00009493147,0.0000183071],"domain_scores_gemma":[0.9996303,0.0001143224,0.00006987047,0.00006571421,0.0001065973,0.00001310544],"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":[0.0002233638,0.0001590649,0.005141726,0.0001475411,0.00004824627,0.0001866954,0.0001523605,0.02270053,0.4898269,0.001029601,0.0006566428,0.4797274],"study_design_scores_gemma":[0.0000145632,0.0002519673,0.02911747,0.00003490007,0.00006826587,0.0009220431,0.00008758309,0.8064964,0.1587591,0.001601217,0.002601548,0.00004492888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1763045,0.0003920247,0.8192003,0.000114422,0.00005429247,0.00004590846,0.0001212779,0.001049433,0.002717859],"genre_scores_gemma":[0.7277198,0.0003270736,0.2677651,0.00009108519,0.00004149166,0.00003687538,0.0002515268,0.00009155442,0.003675466],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001311163,"threshold_uncertainty_score":0.004386246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01950515605421343,"score_gpt":0.2549637781059346,"score_spread":0.2354586220517212,"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."}}