{"id":"W4403130270","doi":"10.1115/1.4066784","title":"Methodology for Modeling Nonlinear Thermomechanical Response With Wear at High-Speed Interactions: Application to a Pin–Disk Configuration","year":2024,"lang":"en","type":"article","venue":"Journal of Engineering for Gas Turbines and Power","topic":"Tribology and Lubrication Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"Agence Nationale de la Recherche","keywords":"Rubbing; Finite element method; Axial symmetry; Mechanics; Rotor (electric); Transient (computer programming); Rotational speed; Mechanical engineering; Aerodynamics; Coupling (piping); Physics; Structural engineering; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004935524,0.0001502782,0.0002352402,0.000255545,0.0000392306,0.00003244882,0.00007165575,0.00008562711,0.000008241642],"category_scores_gemma":[0.0001300578,0.0001230465,0.00007740644,0.0001439946,0.000006847001,0.000185163,0.000009515783,0.0001636105,0.000002178763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007574164,"about_ca_system_score_gemma":0.00001566718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001001802,"about_ca_topic_score_gemma":0.000001349422,"domain_scores_codex":[0.9992945,0.00001564007,0.0003229527,0.0001325866,0.00006841641,0.000165935],"domain_scores_gemma":[0.999108,0.0005588385,0.00003590249,0.00009594495,0.0001150803,0.00008628995],"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":[0.001165563,0.000008185257,0.000001442712,0.0001023429,0.0001264594,0.000001979501,0.0002987779,0.8123267,0.1827197,0.001967639,0.00008612316,0.001195066],"study_design_scores_gemma":[0.0004782185,0.0003942378,0.00006755689,0.0001272849,0.00006731664,0.0001862406,0.0000365154,0.9554508,0.0050086,0.0001125581,0.0379087,0.0001619918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3372956,0.0004687101,0.6609464,0.0005315055,0.0004486914,0.0002107054,0.00001437168,0.00008153723,0.000002535822],"genre_scores_gemma":[0.9329889,0.00004344973,0.06654005,0.00003411117,0.0002314623,0.00005532426,0.00001048135,0.00005182222,0.00004436032],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5956933,"threshold_uncertainty_score":0.5017689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01957490011545143,"score_gpt":0.2759992924413813,"score_spread":0.2564243923259298,"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."}}