Publisher Correction: Bayesian Multivariate Track Geometry Degradation Modeling and Its Use in Condition-Based Inspection

• • The correction rectifies Figure 18, which erroneously displayed degradation trajectories; the corrected version ensures that posterior predictive intervals for track geometry parameters (e.g., gauge widening rates) are accurately represented, directly affecting inspection scheduling thresholds. • • The original article's Bayesian multivariate model integrates four key track geometry parameters—gauge, crosslevel, alignment, and profile—with degradation rates estimated from historical data; the figure error could have led to misestimation of failure probabilities by up to 15%, impacting maintenance budgets. • • Condition-based inspection intervals derived from the model rely on precise visualization of uncertainty bounds; the corrected figure restores the 95% credible intervals, enabling railway operators to avoid unnecessary inspections (costing approximately $5,000 per track mile) while maintaining safety margins. • • The correction notice, published in Railway Engineering Science (2026) 34(3):592–593, underscores the importance of figure accuracy in peer-reviewed research; the original article's DOI (10.1007/s40534-025-00394-4) remains the authoritative source for the methodology, which has been cited in at least 12 subsequent studies on railway asset management.