{"id":"W2115834647","doi":"10.2514/6.2010-9048","title":"Heat Transfer Optimization of Gas Turbine Blades Using an Adjoint Approach","year":2010,"lang":"en","type":"article","venue":"13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference","topic":"Turbomachinery Performance and Optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gas turbines; Heat transfer; Turbine blade; Computer science; Mechanical engineering; Turbine; Mechanics; Engineering; Physics","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000357475,0.0005169134,0.0007501196,0.0009425369,0.0003002828,0.0001525024,0.0004380449,0.0003399068,0.0009297407],"category_scores_gemma":[0.00003248134,0.0005066535,0.0002754647,0.002218011,0.0001812192,0.001651261,0.00006901912,0.0004650224,0.000003314456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006004428,"about_ca_system_score_gemma":0.0000944462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007848053,"about_ca_topic_score_gemma":0.00009031488,"domain_scores_codex":[0.9974049,0.0001020806,0.0009613831,0.0006309497,0.0004417644,0.0004589242],"domain_scores_gemma":[0.9983155,0.00004370156,0.00007075586,0.0007792875,0.0005365142,0.0002542994],"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":[0.00005151311,0.0002734477,0.002677833,0.00009131609,0.0003150129,0.000001662593,0.001077975,0.9840141,0.01109838,0.00009814042,0.000004633909,0.0002960184],"study_design_scores_gemma":[0.0006255301,0.00008191098,0.001064998,0.00002633973,0.0008264303,0.000009348377,0.0002762537,0.9896217,0.006888831,0.00001007685,0.0000050955,0.0005634744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3482962,0.00004165076,0.6502734,0.00002508248,0.0001720183,0.0002798584,0.00004522214,0.0002435091,0.0006230376],"genre_scores_gemma":[0.7685542,0.0001863771,0.2295379,0.00000989925,0.00009472861,0.00002808684,0.00149545,0.00006433389,0.00002901518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4207355,"threshold_uncertainty_score":0.9999835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02095259549799245,"score_gpt":0.2518854294338622,"score_spread":0.2309328339358698,"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."}}