{"id":"W7083592867","doi":"10.1016/j.cma.2025.118357","title":"Geometry-agnostic model reduction with GNN-generated reduced POD bases and boosted PGD enrichment for (non)linear structural elastodynamics","year":2025,"lang":"en","type":"article","venue":"Computer Methods in Applied Mechanics and Engineering","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"Grand Équipement National De Calcul Intensif","keywords":"Point of delivery; Reduction (mathematics); Proper orthogonal decomposition; Finite element method","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":[0.0004429105,0.000237006,0.0002882694,0.0002070851,0.0001026946,0.00008179983,0.0002208105,0.0001131745,3.382791e-7],"category_scores_gemma":[0.00003521944,0.0002230023,0.00002440065,0.0004437915,0.00001059217,0.00007270578,0.0002648541,0.0001904013,5.186407e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004586074,"about_ca_system_score_gemma":0.00004076116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001957006,"about_ca_topic_score_gemma":2.700468e-7,"domain_scores_codex":[0.9988089,0.00001932087,0.0002590806,0.000529155,0.00008057233,0.0003029276],"domain_scores_gemma":[0.9993677,0.0001691838,0.00006166695,0.0002695985,0.00005913041,0.00007270082],"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":[0.0000222008,0.00001414652,0.000001494755,0.0001970702,0.00003535482,0.000001915527,0.0001392276,0.7651214,0.1042721,0.07176045,0.00001155234,0.05842304],"study_design_scores_gemma":[0.0006035038,0.00004447869,0.00002799948,0.0000760371,0.00001691164,0.00001857109,0.0000183539,0.9720563,0.0188562,0.007915107,0.0001310607,0.0002354316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02514343,0.00009018636,0.9737912,0.0001382479,0.0003243579,0.0003508262,0.000002398267,0.0001001985,0.00005915927],"genre_scores_gemma":[0.2618557,0.00002007755,0.7379407,0.00005066688,0.00003667533,0.0000577168,0.000008722108,0.000005981895,0.00002380772],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2367123,"threshold_uncertainty_score":0.909377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246785353761666,"score_gpt":0.2632785417331877,"score_spread":0.250810688195571,"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."}}