{"id":"W4401634280","doi":"10.1115/1.4066223","title":"Robust Design for Product Adaptation Considering Changes in Configurations and Parameters","year":2024,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Product (mathematics); Product design; Tree (set theory); Probabilistic design; Design of experiments; Computer science; Adaptation (eye); Mathematical optimization; Node (physics); Engineering design process; Reliability engineering; Engineering; Mathematics; Mechanical engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00169762,0.001013582,0.0008438785,0.0009763509,0.000337974,0.0009484926,0.0009027288,0.0007000717,0.001996333],"category_scores_gemma":[0.003473283,0.0005738816,0.00119331,0.0007153964,0.0005941403,0.0008016775,0.0008876662,0.0007248292,0.0002617063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007978578,"about_ca_system_score_gemma":0.0008076717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002235362,"about_ca_topic_score_gemma":0.00128158,"domain_scores_codex":[0.9985278,0.0004804841,0.00007661629,0.0003161549,0.0004813467,0.0001175732],"domain_scores_gemma":[0.9987577,0.0005437014,0.0002984257,0.0001487442,0.000224323,0.00002718994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003536149,0.00001542814,0.0002847913,0.00004285488,0.00002136466,0.000041567,0.00002809945,0.9735006,0.004373666,0.003275394,0.00008785581,0.01829301],"study_design_scores_gemma":[0.000005173207,0.00005900755,0.00015381,0.000007208706,0.00001405068,0.00001881082,0.000006158915,0.9959022,0.001307447,0.002031765,0.0004874759,0.00000695498],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02080342,0.000105174,0.9764122,0.00003132333,0.00001062005,0.00005946302,0.00003216789,0.00018267,0.00236305],"genre_scores_gemma":[0.7726724,0.0001509408,0.2249832,0.00003967389,0.00001103267,0.0002553343,0.0001062314,0.0000696195,0.001711684],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002235362,"threshold_uncertainty_score":0.00897795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1215984394177113,"score_gpt":0.2495970128149739,"score_spread":0.1279985733972626,"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."}}