{"id":"W4401330963","doi":"10.1016/j.cma.2024.117254","title":"A hyperreduced reduced basis element method for reduced-order modeling of component-based nonlinear systems","year":2024,"lang":"en","type":"article","venue":"Computer Methods in Applied Mechanics and Engineering","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Autodesk (Canada); University of Toronto","funders":"","keywords":"Component (thermodynamics); Nonlinear system; Basis (linear algebra); Finite element method; Element (criminal law); Mathematics; Applied mathematics; Computer science; Structural engineering; Engineering; Geometry; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008847215,0.0002556047,0.0004488702,0.0002305663,0.00004353673,0.00007351192,0.0001284178,0.0000790687,0.000007465102],"category_scores_gemma":[0.000003626724,0.0002538067,0.0001109769,0.0003093614,0.000004445413,0.00003796284,0.00006820187,0.0002411925,3.501241e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003297616,"about_ca_system_score_gemma":0.00004258343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002009282,"about_ca_topic_score_gemma":7.647389e-8,"domain_scores_codex":[0.9985682,0.00005397029,0.0005033266,0.000450874,0.000115069,0.0003085865],"domain_scores_gemma":[0.9993538,0.0002343685,0.00005938713,0.0002099899,0.00004680346,0.00009571153],"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":[0.00001615412,0.00002448843,2.10568e-7,0.0002324868,0.00006173416,3.411552e-7,0.00007758704,0.7509735,0.08671911,0.0715712,0.00001473058,0.09030841],"study_design_scores_gemma":[0.000440308,0.00002992916,2.73577e-7,0.0002034892,0.00004299281,0.000001696191,0.00006674113,0.9825472,0.01438253,0.001420843,0.0006217256,0.0002422563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005095164,0.0003291061,0.992535,0.00004585499,0.001276329,0.000553099,0.00001743068,0.00008150493,0.00006648915],"genre_scores_gemma":[0.2562694,0.000009612507,0.7431199,0.00001178997,0.0003555415,0.0001607043,0.00002392501,0.00004374511,0.000005357938],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2511742,"threshold_uncertainty_score":0.9999914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03109185572068453,"score_gpt":0.315610667037405,"score_spread":0.2845188113167205,"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."}}