{"id":"W4362712108","doi":"10.5267/j.esm.2023.3.002","title":"The effect of hardness matching of rail/wheel materials on wear rate of railway wheel","year":2023,"lang":"en","type":"article","venue":"Engineering Solid Mechanics","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tread; Materials science; Automotive engineering; Wheel running; Material properties; MATLAB; Blanking; Composite material; Structural engineering; Computer science; Mechanical engineering; Engineering; Natural rubber","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000211848,0.0002375766,0.0002370512,0.0003860818,0.0002025529,0.0003492025,0.0002458095,0.0002841458,0.002323208],"category_scores_gemma":[0.0008918169,0.0001908077,0.0003052829,0.0002366698,0.0001959293,0.0002680989,0.0002660336,0.0001958636,0.0003395841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001895589,"about_ca_system_score_gemma":0.0001178752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001821111,"about_ca_topic_score_gemma":0.003197584,"domain_scores_codex":[0.9997019,0.0000255324,0.0000212446,0.00006774429,0.0001222947,0.00006125969],"domain_scores_gemma":[0.9996616,0.00008555532,0.00007759058,0.00005020265,0.00009672339,0.0000282891],"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":[0.001699448,0.0001683718,0.04726867,0.0003327187,0.00008248335,0.0004297975,0.0002277327,0.02081494,0.8853344,0.0001920717,0.0004860873,0.04296326],"study_design_scores_gemma":[0.00002442407,0.002611924,0.2625245,0.00003136322,0.0001267458,0.0003753817,0.0006535754,0.02291735,0.7074429,0.0001156818,0.003118588,0.00005752785],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997555,0.0002403994,0.001065918,0.00001053097,0.00001623535,0.00000901897,0.00009079097,0.00003601023,0.0009761007],"genre_scores_gemma":[0.9989287,0.00004945951,0.0004032864,0.000005843891,0.000001815813,0.000003111779,0.00005602861,0.00001202279,0.0005397113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002323208,"threshold_uncertainty_score":0.007771909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004124233271884925,"score_gpt":0.2033753925307173,"score_spread":0.1992511592588324,"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."}}