{"id":"W4390863027","doi":"10.1111/ffe.14230","title":"Aerodynamic fatigue evaluation of the equipment cabin of high‐speed trains based on sub‐zone loading method","year":2024,"lang":"en","type":"article","venue":"Fatigue & Fracture of Engineering Materials & Structures","topic":"Aerodynamics and Fluid Dynamics Research","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"National Key Research and Development Program of China; Central South University","keywords":"Structural engineering; Train; Aerodynamics; Stress (linguistics); Finite element method; Stress concentration; Vibration fatigue; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002081379,0.0002770976,0.0001614964,0.0007828383,0.0001829928,0.0001418597,0.0002131294,0.0002156276,0.001122084],"category_scores_gemma":[0.0002680056,0.000126611,0.0001870674,0.0002269529,0.0001444509,0.0002012855,0.0001419841,0.00009347712,0.000135403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001783985,"about_ca_system_score_gemma":0.0001551986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002113363,"about_ca_topic_score_gemma":0.003878387,"domain_scores_codex":[0.9998136,0.00002565565,0.000008051793,0.00002861122,0.0001084407,0.00001558776],"domain_scores_gemma":[0.9997632,0.00004066976,0.0000327207,0.00002142961,0.0001252023,0.00001667904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003759378,0.0001195978,0.03164398,0.0002660061,0.00003683035,0.0002064094,0.000380332,0.07520682,0.7611533,0.0005771756,0.0003942324,0.1296393],"study_design_scores_gemma":[0.00001166681,0.001087635,0.1720473,0.0000186447,0.00004395029,0.0003939338,0.0002642999,0.6922098,0.1325086,0.0002012775,0.00117171,0.00004117172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.910157,0.0001170992,0.08789324,0.00001668614,0.000006038298,0.00003828738,0.00008548974,0.0001367053,0.001549342],"genre_scores_gemma":[0.992939,0.00003612045,0.006544079,0.00000268686,0.000001516905,0.00001120912,0.00003895794,0.000003199815,0.0004232214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002113363,"threshold_uncertainty_score":0.004202068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02124979945693364,"score_gpt":0.2942580113320488,"score_spread":0.2730082118751151,"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."}}