{"id":"W4391173023","doi":"10.1177/09544062231221625","title":"A review on aerodynamic optimization of turbomachinery using adjoint method","year":2024,"lang":"en","type":"review","venue":"Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science","topic":"Turbomachinery Performance and Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Turbomachinery; Aerodynamics; Computer science; Mathematical optimization; Context (archaeology); Multidisciplinary design optimization; Aerospace engineering; Multidisciplinary approach; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002873542,0.0005917734,0.0021196,0.0009476112,0.0000596344,0.00003337131,0.001390163,0.0003301603,0.00001037808],"category_scores_gemma":[0.001371429,0.0003962415,0.0009567272,0.002804891,0.0001352105,0.0005691385,0.000206019,0.001218253,0.000001343577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004238441,"about_ca_system_score_gemma":0.0004104409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001528271,"about_ca_topic_score_gemma":9.169066e-8,"domain_scores_codex":[0.9955902,0.00002277993,0.002458361,0.0003539097,0.001178753,0.0003959678],"domain_scores_gemma":[0.9975218,0.0001228787,0.001232649,0.0003026365,0.0006237039,0.0001963736],"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":[0.000009052676,0.00004631842,2.430822e-8,0.0369468,0.0001507583,0.00000113514,0.00001329124,0.9409146,0.002484747,0.009561453,0.00007402209,0.009797838],"study_design_scores_gemma":[0.0001938424,0.0001934771,1.079302e-7,0.1123611,0.001437903,0.0002236105,0.000005026469,0.8757386,0.004238828,0.00005904094,0.005188922,0.0003596025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000146574,0.8138226,0.1820847,0.00002948179,0.003002661,0.0006932194,0.00003949235,0.00009979327,0.00008141519],"genre_scores_gemma":[0.004652608,0.9462759,0.04877039,0.00001674767,0.0001801263,0.00001223433,0.000003370679,0.0000846096,0.000004051167],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.1333144,"threshold_uncertainty_score":0.999849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0246994451951221,"score_gpt":0.2949549205827672,"score_spread":0.2702554753876452,"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."}}