{"id":"W4410925935","doi":"10.1007/s00707-025-04371-0","title":"Uncertainty quantification of local elastic properties in additively manufactured materials for topology optimization applications using machine learning","year":2025,"lang":"en","type":"article","venue":"Acta Mechanica","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Autodesk","keywords":"Solid mechanics; Topology optimization; Materials science; Topology (electrical circuits); Computer science; Mathematical optimization; Mechanical engineering; Artificial intelligence; Composite material; Mathematics; Structural engineering; Engineering; Finite element method; Combinatorics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001098758,0.0007248034,0.0007961934,0.0009194648,0.0002791132,0.0009242689,0.0007812742,0.0008831953,0.0007646118],"category_scores_gemma":[0.003180261,0.0005184038,0.0006261187,0.0006023917,0.001011327,0.00169186,0.001131957,0.0009477612,0.0001402304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005765796,"about_ca_system_score_gemma":0.0003938419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006472798,"about_ca_topic_score_gemma":0.0009153988,"domain_scores_codex":[0.9994739,0.0001242054,0.00002327411,0.000105433,0.0002422985,0.00003099226],"domain_scores_gemma":[0.9984453,0.000984887,0.0002138477,0.000168462,0.0001494607,0.00003798223],"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":[0.00006053028,0.00003408812,0.0005110943,0.0000792385,0.00002919228,0.00004109918,0.00003210753,0.955112,0.01130872,0.007188852,0.0001318118,0.02547129],"study_design_scores_gemma":[0.000001078743,0.00001284846,0.0002224435,0.000003983643,0.000003826833,0.000009149957,0.000003770551,0.9935091,0.002643725,0.003481659,0.0001035813,0.000004784842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05015087,0.0002498439,0.9482465,0.00007688013,0.00001488526,0.00001161964,0.00004169716,0.0001584797,0.001049215],"genre_scores_gemma":[0.9333487,0.0002340404,0.06517498,0.00003415253,0.00002826658,0.00004213122,0.0001075651,0.00009265498,0.0009375021],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001098758,"threshold_uncertainty_score":0.005810797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01672402138805878,"score_gpt":0.2376137228317581,"score_spread":0.2208897014436993,"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."}}