{"id":"W7108341504","doi":"10.1115/imece-india2025-161958","title":"Rotor Stress Prediction Using Convolutional Neural Network","year":2025,"lang":"","type":"article","venue":"","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Siemens (Canada)","funders":"","keywords":"Rotor (electric); Convolutional neural network; Artificial neural network; Margin (machine learning); Deep learning; Turbine; Key (lock); Finite element method","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001705425,0.0005523997,0.0003235577,0.0003551231,0.0001315751,0.0004172527,0.0006475661,0.0005176977,0.001130581],"category_scores_gemma":[0.0004563768,0.0002701009,0.0003585072,0.0002268785,0.000225714,0.0004010471,0.0002503681,0.0005066338,0.0003150158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005911317,"about_ca_system_score_gemma":0.0004102312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01008847,"about_ca_topic_score_gemma":0.009482058,"domain_scores_codex":[0.9999398,0.000007041625,0.00000290051,0.00002030482,0.00001831061,0.00001167791],"domain_scores_gemma":[0.9998645,0.00004725479,0.00001860853,0.0000113254,0.00004926879,0.000009180658],"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":[0.0000364059,0.00003205892,0.001179487,0.00001880112,0.00002147932,0.00003364694,0.000007379158,0.9670135,0.003363026,0.0004850526,0.0005939706,0.02721515],"study_design_scores_gemma":[3.548531e-7,0.000003123323,0.00008306265,7.44223e-7,8.682712e-7,0.000001122677,3.649099e-7,0.999564,0.0002264067,0.00008330589,0.00003592278,7.263117e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2979297,0.001173423,0.689682,0.0007323468,0.0001592716,0.00004498005,0.00051853,0.00270776,0.007051978],"genre_scores_gemma":[0.981752,0.0001587293,0.0151383,0.000072377,0.00001738881,0.00002336538,0.0002863538,0.00002752355,0.002523814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01008847,"threshold_uncertainty_score":0.02005953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01977613399759118,"score_gpt":0.2688415433818198,"score_spread":0.2490654093842286,"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."}}