{"id":"W1566833990","doi":"10.1007/978-94-017-0161-7_42","title":"A Model-Based Framework for Robust Design","year":2003,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Design matrix; Inverse; Logarithm; Robustness (evolution); Mathematics; Matrix (chemical analysis); Bandwidth (computing); Set (abstract data type); Computer science; Mathematical optimization; Algorithm; Applied mathematics; Statistics; Mathematical analysis; Regression analysis; Telecommunications; Geometry","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":[0.0007913623,0.001839521,0.001516082,0.0007122179,0.0004377866,0.001496593,0.002240411,0.00162729,0.007117212],"category_scores_gemma":[0.001683629,0.001052285,0.001607679,0.0008647227,0.0009850214,0.001526095,0.001404408,0.002380507,0.003356405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006188393,"about_ca_system_score_gemma":0.0006391123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001667627,"about_ca_topic_score_gemma":0.001810431,"domain_scores_codex":[0.9994185,0.0001608703,0.00003030362,0.00009247269,0.0002719666,0.00002591264],"domain_scores_gemma":[0.9996909,0.0001289258,0.0000333218,0.00006773644,0.00006828679,0.00001080186],"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":[0.00003644187,0.00003779686,0.00006700667,0.000321164,0.00008213525,0.00009366517,0.00005210776,0.5209764,0.006020128,0.3261736,0.008930163,0.1372094],"study_design_scores_gemma":[0.00001348738,0.00004812209,0.0000466156,0.00004897724,0.00003153466,0.00009202705,0.00000795006,0.8028106,0.001515602,0.1721086,0.02325683,0.00001968625],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001092181,0.0002742797,0.9971113,0.00004812077,0.00002829859,0.000008354977,0.00001792861,0.0001588437,0.002243564],"genre_scores_gemma":[0.07661853,0.002257122,0.9054115,0.0002523864,0.0002451341,0.0003422773,0.0002571972,0.0004175674,0.01419825],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007117212,"threshold_uncertainty_score":0.02380943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07856166619759361,"score_gpt":0.2824109632491055,"score_spread":0.2038492970515119,"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."}}