{"id":"W2329999159","doi":"10.2514/6.2004-4631","title":"Sequential Optimization Algorithms for Aerodynamic Shape Optimization","year":2004,"lang":"en","type":"article","venue":"10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Aerodynamics; Computer science; Optimization algorithm; Algorithm; Mathematical optimization; Mathematics; Engineering; Aerospace 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002831665,0.0005185739,0.0006039813,0.000691749,0.0005780895,0.0004143296,0.0002798439,0.0002989167,0.0006063159],"category_scores_gemma":[0.00005936521,0.0005360428,0.0002274685,0.001216895,0.0001097002,0.0009900451,0.0001027397,0.0001940869,0.000003457566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001510033,"about_ca_system_score_gemma":0.00008929183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003697052,"about_ca_topic_score_gemma":0.00005846959,"domain_scores_codex":[0.9975799,0.00004850958,0.0007665299,0.0007729143,0.0003316849,0.0005005053],"domain_scores_gemma":[0.998544,0.00006602959,0.0002468833,0.0003945752,0.0005118137,0.000236636],"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":[0.00004535581,0.00007563405,0.000180096,0.0001260525,0.0003379002,0.00000221803,0.0004177874,0.9963339,0.00003061851,0.0002932187,0.0000083881,0.002148808],"study_design_scores_gemma":[0.00139793,0.00009616259,0.0003737572,0.0000553076,0.0007840939,0.000004628094,0.0001430721,0.9959853,0.0003749793,0.0001236563,0.00001962678,0.00064154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005776908,0.0002170167,0.9919055,0.0002179144,0.0002702069,0.0007089988,0.0001114904,0.0004913993,0.0003005573],"genre_scores_gemma":[0.4896307,0.001135536,0.5067724,0.00002789011,0.00009881787,0.0001393204,0.002028145,0.0000691985,0.0000980538],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4851331,"threshold_uncertainty_score":0.9997091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01919347691594712,"score_gpt":0.2589343534403013,"score_spread":0.2397408765243542,"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."}}