{"id":"W2139481431","doi":"10.1115/1.1610014","title":"A New Scaling Method for Component Maps of Gas Turbine Using System Identification","year":2003,"lang":"en","type":"article","venue":"Journal of Engineering for Gas Turbines and Power","topic":"Scientific Research and Discoveries","field":"Physics and Astronomy","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Pratt and Whitney Canada","keywords":"Scaling; Turboprop; Envelope (radar); Flight envelope; Point (geometry); Component (thermodynamics); Computer science; Turbine; Operating point; Aero engine; Performance prediction; Engineering; Simulation; Automotive engineering; Aerospace engineering; Mechanical engineering; Mathematics; Aerodynamics; Electronic engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006285476,0.00009826366,0.0002392077,0.0001185687,0.00005383429,0.00008055838,0.00007783246,0.00002204754,0.00001325958],"category_scores_gemma":[0.00005584391,0.00007791785,0.0001623518,0.00009629956,0.00001093475,0.0001586168,0.00001018663,0.00005867286,1.484173e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001878132,"about_ca_system_score_gemma":0.00005811841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002354833,"about_ca_topic_score_gemma":1.714384e-7,"domain_scores_codex":[0.9991788,0.00001416906,0.0003921223,0.0000977098,0.0001463364,0.0001708637],"domain_scores_gemma":[0.9992405,0.0001204861,0.0002257267,0.00009023029,0.0002125959,0.0001104905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006521512,0.0002359398,0.003178599,0.001687029,0.0008500431,0.000004163441,0.001463104,0.1371129,0.6338127,0.203813,0.009132532,0.008057769],"study_design_scores_gemma":[0.009768008,0.0009850293,0.001544048,0.002025498,0.0006282288,0.0002269278,0.004947608,0.323068,0.54827,0.01416998,0.09325258,0.001114119],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2466397,0.0004191498,0.7520762,0.00003503125,0.0005721215,0.0001655603,0.000043646,0.000003699613,0.00004489667],"genre_scores_gemma":[0.8854648,0.00000320373,0.1141459,0.000002031173,0.0002202418,0.000004176025,0.000009306716,0.0000153579,0.0001350404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6388251,"threshold_uncertainty_score":0.3177398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01697105503088182,"score_gpt":0.2876275297231194,"score_spread":0.2706564746922376,"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."}}