{"id":"W1593901098","doi":"10.1007/978-3-540-30217-9_81","title":"Multi-objective Optimization of a Composite Material Spring Design Using an Evolutionary Algorithm","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Mechanical Engineering and Vibrations Research","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Spring (device); Evolutionary algorithm; Algorithm; Optimization algorithm; Composite number; Mathematical optimization; Artificial intelligence; Mechanical engineering; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001029083,0.0009461977,0.001235564,0.001079445,0.0006182657,0.000880965,0.001234778,0.002202168,0.003655721],"category_scores_gemma":[0.001521084,0.0008044534,0.001108005,0.0008657707,0.0005579239,0.0006735557,0.0008438954,0.0008187782,0.0004257155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005561416,"about_ca_system_score_gemma":0.0007507636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001380629,"about_ca_topic_score_gemma":0.001948811,"domain_scores_codex":[0.9997124,0.00007725104,0.00001205057,0.00004330556,0.0001259547,0.00002898616],"domain_scores_gemma":[0.9994373,0.0003135801,0.00006302914,0.00003063282,0.0001236617,0.00003183772],"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":[0.0000319253,0.00004203543,0.0001102415,0.00004607646,0.00002106213,0.00003845208,0.00001663549,0.9807135,0.002897402,0.001661361,0.000138823,0.01428247],"study_design_scores_gemma":[0.000007969265,0.00003525169,0.00005648929,0.000003546063,0.000007275625,0.000009217026,0.0000036632,0.9990016,0.0003698841,0.0003090808,0.0001934018,0.000002636628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04129314,0.0002715414,0.9501859,0.00008415707,0.0000693801,0.0000964572,0.00003084413,0.0001538863,0.007814725],"genre_scores_gemma":[0.4466996,0.0002674173,0.5442515,0.00007202558,0.00005576869,0.0004971742,0.00007716133,0.0001246255,0.007954799],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003655721,"threshold_uncertainty_score":0.01222962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02844024930183098,"score_gpt":0.2579737030981095,"score_spread":0.2295334537962785,"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."}}