{"id":"W4411665802","doi":"10.1016/j.geits.2025.100332","title":"Toward smart railway maintenance: AI-enhanced Non-Destructive Evaluation using Vision Transformers and CNNs for fastener defect detection","year":2025,"lang":"en","type":"article","venue":"Green Energy and Intelligent Transportation","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; Université du Québec à Rimouski","funders":"Science and Engineering Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial intelligence; Computer science; Deep learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001873702,0.0002174607,0.000202778,0.0001918422,0.000151467,0.00003181297,0.00004239086,0.0001528836,0.000005604864],"category_scores_gemma":[0.000007281455,0.0002074276,0.00009453634,0.0001926224,0.00005195184,0.0003308684,0.000002119964,0.0001022968,1.655931e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001193369,"about_ca_system_score_gemma":0.00002833017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002292162,"about_ca_topic_score_gemma":0.000669747,"domain_scores_codex":[0.9989957,0.00001866308,0.0003118413,0.0002816823,0.0001393966,0.0002527616],"domain_scores_gemma":[0.9996226,0.00003035454,0.00004247304,0.00007506521,0.0001788874,0.00005056256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002829886,0.00001109883,0.0002746075,0.0003465158,0.0001779849,0.000001005504,0.00189953,0.04255529,0.1387668,0.001751694,0.00001797725,0.8139145],"study_design_scores_gemma":[0.001535846,0.0002424297,0.015307,0.0004282618,0.000445702,0.000005093324,0.001305825,0.3257591,0.6433196,0.009568017,0.001584844,0.0004983445],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.390288,0.000200588,0.6084754,0.00001970536,0.0005127511,0.0002462366,0.00001039817,0.00004308868,0.0002037714],"genre_scores_gemma":[0.9983729,0.0003727811,0.0008832057,0.00006148821,0.00008289959,0.00009878933,0.00007066789,0.00002507699,0.00003219193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8134162,"threshold_uncertainty_score":0.8458651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01042490137910379,"score_gpt":0.2506945964137462,"score_spread":0.2402696950346424,"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."}}