{"id":"W2132447661","doi":"10.4028/www.scientific.net/amm.24-25.337","title":"Finite Element Model Updating of a Thin Wall Enclosure under Impact Excitation","year":2010,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council","keywords":"Finite element method; Enclosure; Discretization; Excitation; Lanczos resampling; Structural engineering; Constant (computer programming); Mechanics; Shell (structure); Natural frequency; Engineering; Mathematical analysis; Mathematics; Computer science; Physics; Mechanical engineering; Acoustics; Vibration; Eigenvalues and eigenvectors","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":[0.0002682262,0.0001203266,0.0001731361,0.00004701407,0.00003363503,0.00002313791,0.00007085282,0.0001051805,0.00003177669],"category_scores_gemma":[0.000008244901,0.000105977,0.00001559189,0.0000387849,0.000004423069,0.00004512621,0.00003266749,0.00008488147,0.000001211468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002187739,"about_ca_system_score_gemma":0.00001294856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003186622,"about_ca_topic_score_gemma":0.000004429526,"domain_scores_codex":[0.9993659,0.00000593047,0.0002594714,0.0001092758,0.00009536761,0.0001641166],"domain_scores_gemma":[0.9996817,0.00003029068,0.00006927242,0.0001463449,0.00002501457,0.0000474404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000009184113,0.000002704529,8.279807e-7,0.0001157737,0.00001025144,1.034329e-7,0.0001869527,0.001853094,0.7619056,0.2347839,0.00003099778,0.001100606],"study_design_scores_gemma":[0.0001967159,0.00003522842,0.0001766733,0.00002433748,0.00001406451,0.000001418296,0.00005478932,0.06568698,0.5279884,0.4056393,0.0000206912,0.0001613989],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9398713,0.00001020936,0.05923333,0.00001183496,0.0002954548,0.0002610823,0.00003390146,0.0001783735,0.0001045326],"genre_scores_gemma":[0.9384495,0.00005234869,0.06133112,0.00002232328,0.00005728462,0.00004257963,0.00001785623,0.00002518438,0.000001785228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2339172,"threshold_uncertainty_score":0.4321616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01528179869389559,"score_gpt":0.273490658483059,"score_spread":0.2582088597891634,"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."}}