{"id":"W2083130261","doi":"10.1115/detc2005-84425","title":"Modeling of Non-Linear Relations Among Different Design Evaluation Measures for Multi-Objective Design Optimization","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Weighting; Relation (database); Measure (data warehouse); Computer science; Calipers; Design of experiments; Multi-objective optimization; Evaluation methods; Design methods; Mathematical optimization; Mathematics; Reliability engineering; Data mining; 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":[0.006201927,0.002365254,0.001271138,0.001433149,0.0004115773,0.001208075,0.001688426,0.001116037,0.001239432],"category_scores_gemma":[0.01252484,0.001028963,0.001431944,0.001370801,0.0009625839,0.002330364,0.001072141,0.002112835,0.0003729478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001207955,"about_ca_system_score_gemma":0.001130582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001916616,"about_ca_topic_score_gemma":0.001993685,"domain_scores_codex":[0.9953359,0.002468917,0.0001719491,0.0004855558,0.00139883,0.0001389239],"domain_scores_gemma":[0.9929906,0.005255763,0.0008132762,0.0003156223,0.0005726895,0.00005211049],"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":[0.00002373329,0.00004439819,0.0003093706,0.0001043151,0.0000477787,0.00002983398,0.00005770593,0.9695738,0.001496175,0.008869731,0.0000874683,0.01935566],"study_design_scores_gemma":[0.000003121017,0.00003040144,0.0001017442,0.000007138905,0.00000739699,0.000008751934,0.000004360722,0.9962797,0.0004225684,0.002918877,0.0002094701,0.000006524043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003758714,0.00008880654,0.9956245,0.00002564765,0.000005969195,0.00002569299,0.000006675154,0.00004842605,0.0004155913],"genre_scores_gemma":[0.4066449,0.0004534523,0.5891194,0.00008097263,0.00003696606,0.0007552995,0.00009089665,0.0001234955,0.002694651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006201927,"threshold_uncertainty_score":0.0327993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09695934750448543,"score_gpt":0.3319777351398806,"score_spread":0.2350183876353952,"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."}}