{"id":"W2071012667","doi":"10.1177/1077546308097269","title":"Optimization of Mechatronic Design Quotient Using Genetic Algorithm in Vibration Controllers for Flexible Beams","year":2009,"lang":"en","type":"article","venue":"Journal of Vibration and Control","topic":"Aeroelasticity and Vibration Control","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Control theory (sociology); Genetic algorithm; Optimal design; Damper; Vibration control; Controller (irrigation); Mechatronics; Vibration; Benchmark (surveying); Active vibration control; Control engineering; Linear-quadratic regulator; Engineering; Optimal control; Computer science; Mathematical optimization; Mathematics; Control (management); Artificial intelligence","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":[0.0003146001,0.0001256438,0.0003403882,0.0002321203,0.00005038765,0.00004999007,0.00006111904,0.00009177649,0.00001412171],"category_scores_gemma":[0.00005967035,0.000119558,0.00008185842,0.0001310247,0.00001589426,0.0004848499,0.000002085649,0.00009767185,1.888519e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006521173,"about_ca_system_score_gemma":0.00007907184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000014402,"about_ca_topic_score_gemma":0.000001109271,"domain_scores_codex":[0.9988339,0.00006727134,0.0006980488,0.000085921,0.000164773,0.0001501135],"domain_scores_gemma":[0.9992857,0.0001278322,0.0002894964,0.00005990811,0.0001730842,0.00006395652],"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":[0.0002397684,0.00004069246,0.00001484322,0.00001234228,0.00003861424,7.642436e-7,0.0001147456,0.9621485,0.02634684,0.0002577583,0.00001826579,0.01076682],"study_design_scores_gemma":[0.005649705,0.000642069,0.0004120748,0.00004588254,0.00007417026,0.00001042851,0.00007817518,0.9862746,0.006188578,0.0005073324,0.00001451338,0.0001024483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004389576,0.0006566438,0.994013,0.0002337468,0.0001738791,0.0004941092,0.000006288418,0.00002042711,0.00001237551],"genre_scores_gemma":[0.8426331,0.00008519754,0.1569718,0.0001629734,0.0001230466,0.000006685451,0.000002755961,0.00001123831,0.000003142731],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8382435,"threshold_uncertainty_score":0.4875432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01319760536048462,"score_gpt":0.2259636518241305,"score_spread":0.2127660464636459,"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."}}