{"id":"W4395480881","doi":"10.1016/j.ymssp.2024.111408","title":"Damping prediction of highly dissipative meta-structures through a wave finite element methodology","year":2024,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Fluid Dynamics Simulations and Interactions","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Franche-Comté; Centre Lyonnais d'Acoustique, Université de Lyon; Université de Lyon; Agence Nationale de la Recherche","keywords":"Dissipative system; Finite element method; Structural engineering; Physics; Mathematics; Mathematical analysis; Mechanics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002265535,0.0001442872,0.0003210696,0.00008236703,0.00009627281,0.000106705,0.00004130871,0.00009190704,0.00004915854],"category_scores_gemma":[0.00002567696,0.0001078613,0.0000862294,0.0001736869,0.00002283024,0.0002839823,0.00002403142,0.000176157,9.462125e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004440603,"about_ca_system_score_gemma":0.00001671374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005305305,"about_ca_topic_score_gemma":0.000004174991,"domain_scores_codex":[0.9990051,0.00008100821,0.0004289761,0.0002005348,0.0001354956,0.0001489029],"domain_scores_gemma":[0.9994953,0.0002866733,0.00004510872,0.00007233959,0.00006055119,0.00004006705],"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":[0.00003185821,0.00003879419,0.00001491184,0.003139646,0.002061195,0.00001620374,0.003315045,0.6376596,0.1506924,0.1731243,0.000174298,0.02973173],"study_design_scores_gemma":[0.00007623004,0.00006454632,0.00001474968,0.0001955996,0.0002946077,0.00001646471,0.0002436634,0.9891297,0.001911116,0.006537901,0.001422107,0.00009333464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009160114,0.006328036,0.9832771,0.00003184107,0.0003773487,0.0001623792,0.00007136755,0.0001602982,0.0004315249],"genre_scores_gemma":[0.9921216,0.0000627639,0.007557541,0.00000795891,0.0001114436,0.00004658997,0.00001702788,0.00002213512,0.00005289339],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9829615,"threshold_uncertainty_score":0.4398457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09342672564399042,"score_gpt":0.3055637612081159,"score_spread":0.2121370355641255,"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."}}