A Mathematical-Statistical Method for EPMA U-Th-Pb Chemical Age Data Analysis of Pitchblende

Pitchblende is prone to Pb substitution and/or U loss, resulting in deviations in chemical ages based on the electron probe microanalysis (EPMA) U-Th-^totalPb method. Although previous studies have attempted to correct chemical ages through linear regression, they generally lack a systematic statistical framework, particularly in data preprocessing and outlier identification, which limits the reliability of the results. In this study, the Xiwang uranium deposit in the Xiazhuang orefield, northern Guangdong, was selected as the research object, and a mathematical-statistics-based workflow for chemical age processing was developed to address these deficiencies. Spearman rank correlation tests were employed to verify the Pb-substitutions, while K-means clustering and Gaussian mixture modeling (GMM) were applied to identify latent subgroups within the dataset. After excluding anomalous data, a linear regression model was constructed to extrapolate the chemical ages to the point where Pb-substitutions were negligible, thus estimating the crystallization ages of pitchblende. The results indicate that the SiO₂ + FeO model provides the best fit, yielding two extrapolated ages of 102.39 ± 5.88 Ma and 56.87 ± 3.61 Ma, corresponding respectively to the second-phase (second-stage) and fourth-phase mineralization events of the Xiazhuang orefield, both of which have reasonable geological significance. Samples significantly affected by U loss exhibit systematically overestimated chemical ages, while GMM decomposition of these data reveals subpopulation ages indicative of complex hydrothermal overprinting. The proposed workflow of “statistical analysis−model optimization−geological interpretation” effectively enhances the stability and reliability of EPMA U-Th-^totalPb chemical dating and provides a new methodological and interpretive framework for age determination of pitchblende in granite-related uranium deposits.