{"id":"W4231125518","doi":"10.1115/detc2020-22458","title":"Scalable Set-Based Design Optimization and Remanufacturing for Meeting Changing Requirements","year":2020,"lang":"en","type":"article","venue":"","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Scalability; Component (thermodynamics); Remanufacturing; Computer science; Set (abstract data type); Parametric statistics; Process (computing); Functional requirement; Engineering design process; Reliability engineering; Systems engineering; Industrial engineering; Manufacturing engineering; Engineering; Software engineering; Mechanical engineering","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":[0.0001508621,0.0001302649,0.0001192449,0.00007305973,0.0001238184,0.00008263347,0.00005924779,0.00005094596,0.00004765029],"category_scores_gemma":[0.00003866971,0.0001312248,0.0000206975,0.0001023661,0.000007081017,0.0001943595,0.00001860196,0.0000438079,0.000001735741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002362672,"about_ca_system_score_gemma":0.000007069039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001958372,"about_ca_topic_score_gemma":3.436126e-7,"domain_scores_codex":[0.999319,0.000009062578,0.0001646151,0.0001845586,0.00008973646,0.0002330202],"domain_scores_gemma":[0.9997496,0.00004613277,0.000030859,0.00006469441,0.00002774509,0.00008094354],"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":[0.00001032928,0.000001865029,0.00001853271,0.0002989814,0.00000936239,2.922971e-7,0.0001962884,0.9977942,0.0002906005,0.00001495303,0.0001382337,0.001226349],"study_design_scores_gemma":[0.0003542227,0.00002514411,0.000004051199,0.00004011649,0.00001245312,2.270866e-7,0.0000452356,0.8634586,0.1356506,0.00001665443,0.0002535393,0.0001391906],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002146569,0.00008532354,0.9959809,0.0001954453,0.00006034757,0.0003389052,0.000002193518,0.0004490006,0.0007413036],"genre_scores_gemma":[0.6462879,0.00002921937,0.3531851,0.0002702007,0.00007157814,0.0000418756,0.0000236111,0.00004393261,0.00004663048],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6441413,"threshold_uncertainty_score":0.535119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03937179238052269,"score_gpt":0.231245444727818,"score_spread":0.1918736523472953,"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."}}