{"id":"W4388873627","doi":"10.1115/detc2023-114687","title":"Fairness- and Uncertainty-Aware Data Generation for Data-Driven Design","year":2023,"lang":"en","type":"article","venue":"","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Property (philosophy); Sampling (signal processing); Data mining; Generative Design; Selection (genetic algorithm); Generative model; Grid; Bayesian probability; Generative grammar; Machine learning; Artificial intelligence; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005596017,0.001089269,0.001050852,0.001304328,0.000554001,0.001078287,0.001768865,0.001087566,0.001987245],"category_scores_gemma":[0.01367095,0.0006798594,0.001341849,0.0008008315,0.001118614,0.001202374,0.001558174,0.001401483,0.0003803727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001231899,"about_ca_system_score_gemma":0.001720003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00175152,"about_ca_topic_score_gemma":0.002517776,"domain_scores_codex":[0.9975173,0.001022757,0.0001232162,0.0004367513,0.0007661665,0.0001337764],"domain_scores_gemma":[0.9902986,0.006322024,0.0005828372,0.001547358,0.001044978,0.0002041248],"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":[0.0001394963,0.0001013128,0.002876604,0.0001484381,0.00003862973,0.00006009653,0.00009085076,0.910647,0.004057453,0.0107635,0.001071991,0.07000463],"study_design_scores_gemma":[0.00001506015,0.00003556277,0.0001778999,0.000009319171,0.000004756709,0.00001612841,0.000008917945,0.9867921,0.00257267,0.00960266,0.0007578207,0.000007028337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01641972,0.0001656583,0.9816056,0.0001287152,0.00001878724,0.00009152675,0.0001674776,0.000683556,0.0007190128],"genre_scores_gemma":[0.5532361,0.0001186685,0.4441338,0.0001933607,0.00003043856,0.0004651606,0.0008751774,0.0002098463,0.0007375526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005596017,"threshold_uncertainty_score":0.0295949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1575439112816699,"score_gpt":0.2955893569451875,"score_spread":0.1380454456635176,"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."}}