{"id":"W4319589234","doi":"10.1115/imece2022-95195","title":"Uncertainty Quantification in Material Properties of Additively Manufactured Materials for Application in Topology Optimization","year":2022,"lang":"en","type":"article","venue":"","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Randomness; Materials science; Digital image correlation; Modulus; Elastic modulus; Material properties; Fusion; Random field; Young's modulus; Composite material; Algorithm; Computer science; Mathematics; Statistics","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":[0.0002549166,0.00008950983,0.0001645263,0.0002001336,0.00003627848,0.00000884405,0.0001366079,0.00005855096,0.0001368855],"category_scores_gemma":[0.00005375684,0.00008812463,0.0000157966,0.00009825906,0.00003713224,0.00004833623,0.00005525501,0.00006431072,8.230981e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001304933,"about_ca_system_score_gemma":0.00001045722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000206748,"about_ca_topic_score_gemma":0.0000628768,"domain_scores_codex":[0.9993098,0.00003959487,0.0002859636,0.0001532525,0.000074405,0.0001369584],"domain_scores_gemma":[0.999746,0.0000295623,0.00006212441,0.0001307503,0.00002549636,0.000006130163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001065304,0.00003429167,0.00004157081,0.0001008417,0.000007124626,2.473033e-7,0.0001808465,0.8636748,0.1296831,0.001739121,0.0001299057,0.004301698],"study_design_scores_gemma":[0.0002599336,0.00003489318,0.001213861,0.00001091718,0.00000252268,8.935679e-7,0.0004941992,0.04072341,0.9559256,0.000760077,0.000464801,0.0001088273],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9584218,0.00001228072,0.04007407,0.0001116138,0.0001985849,0.0006196536,0.0001915272,0.0002500053,0.0001204452],"genre_scores_gemma":[0.9962063,0.00000871502,0.002597067,0.000006996735,0.0000145458,0.0009161549,0.0002164665,0.00001520745,0.00001858423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8262426,"threshold_uncertainty_score":0.3593618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01910220828133496,"score_gpt":0.2235203581337436,"score_spread":0.2044181498524087,"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."}}