{"id":"W4411341495","doi":"10.1016/j.triboint.2025.110903","title":"Machine learning approach to the assessment and prediction of solid particle erosion of metals","year":2025,"lang":"en","type":"article","venue":"Tribology International","topic":"Erosion and Abrasive Machining","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Safran Electronics (Canada); Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Erosion; Particle (ecology); Materials science; Metallurgy; Environmental science; Forensic engineering; Engineering; Geology; Oceanography; Geomorphology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001425496,0.0004826008,0.0006951473,0.001104231,0.000347791,0.000872041,0.001045109,0.001144055,0.0008428146],"category_scores_gemma":[0.003814902,0.0002552606,0.0004973272,0.0006444053,0.0005177478,0.0005603629,0.0004257555,0.001258849,0.0001791904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008052652,"about_ca_system_score_gemma":0.0007926165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007738547,"about_ca_topic_score_gemma":0.004727175,"domain_scores_codex":[0.9996093,0.0001539771,0.00003332362,0.00007312655,0.0000945103,0.00003572301],"domain_scores_gemma":[0.9971507,0.002269476,0.000140437,0.00006327306,0.0003284077,0.00004777536],"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":[0.00007201741,0.0002017901,0.004214259,0.00005544758,0.00008414502,0.00004691888,0.00003834904,0.9015169,0.001116941,0.003280444,0.0005431716,0.0888296],"study_design_scores_gemma":[0.000001708768,0.00001192359,0.00028013,0.000001560052,0.000002343779,0.000003997335,0.000002940989,0.9984728,0.0001324978,0.001028251,0.00005992038,0.000001934128],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2022227,0.001778208,0.7914245,0.000835158,0.0001005695,0.00009210376,0.0001748037,0.0003458006,0.003026129],"genre_scores_gemma":[0.9341986,0.0004195956,0.06191164,0.00008267655,0.00013886,0.00007966121,0.0001512229,0.00001375983,0.003003911],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007738547,"threshold_uncertainty_score":0.01538706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02133982119094384,"score_gpt":0.3112745001958199,"score_spread":0.289934679004876,"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."}}