{"id":"W2117739475","doi":"10.1177/1045389x13504478","title":"Design optimization of magnetorheological fluid valves using response surface method","year":2013,"lang":"en","type":"article","venue":"Journal of Intelligent Material Systems and Structures","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; Concordia University","funders":"","keywords":"Magnetorheological fluid; Magnetorheological damper; Response surface methodology; Damper; Sequential quadratic programming; Optimal design; Control theory (sociology); Engineering; Structural engineering; Computer science; Quadratic programming; Mathematics; Mathematical optimization","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":[0.0007652867,0.0001296257,0.0004002902,0.00006762052,0.00003960508,0.00009568868,0.00009870728,0.0001392123,0.0003590132],"category_scores_gemma":[0.00009064558,0.0000796815,0.00006940998,0.00005525175,0.00004330257,0.0001509034,0.00001814101,0.00007795353,7.670805e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002100602,"about_ca_system_score_gemma":0.00002072182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003261004,"about_ca_topic_score_gemma":8.188596e-8,"domain_scores_codex":[0.9984131,0.000479461,0.0007591012,0.00007729758,0.0001501686,0.0001209129],"domain_scores_gemma":[0.9993116,0.0001697807,0.0001815089,0.00007118904,0.0001853902,0.00008051856],"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":[0.0002102967,0.000004073045,0.00005535699,0.00003238767,0.00004709523,0.000002407751,0.00005627842,0.6623487,0.3364806,0.0003838831,0.0001073763,0.0002715995],"study_design_scores_gemma":[0.0003401698,0.0006062372,0.001864497,0.00007288272,0.00005153129,0.0002496565,0.0001790335,0.8949615,0.1005389,0.0008256661,0.0001269425,0.0001828953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4881088,0.0008683552,0.5099068,0.00001245201,0.00096323,0.0001159264,0.000002766214,0.00001143217,0.00001021767],"genre_scores_gemma":[0.9227079,0.0002107446,0.07683547,0.000007550073,0.0002045759,9.448018e-7,6.894055e-7,0.000009876759,0.00002228454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.434599,"threshold_uncertainty_score":0.3930943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02222953374058207,"score_gpt":0.2494233488816645,"score_spread":0.2271938151410825,"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."}}