## 5 Conclusions  
In this study, the 3D prospectivity modeling with incorporating spatial analysis data and ore-forming computational simulation data through Bayesian decomposition modeling was conducted in the Xiadian orogenic gold deposit. The results of spatial analysis of the ore-controlling Zhaoping fault find its significant influence on ore shooting or branching, which is primarily driven by variations in fault dip or strike. Most gold mineralization tends to concentrate in the convex areas of the fault zone. The numerical modeling results demonstrate that gold mineralization at Xiadian is closely linked to high rock permeability, but its localization is also influenced by the combination of dilation and shrinkage. Using multiple statistic examinations, this approach is proved to outperform traditional prospectivity modeling methods, likely due to the more systematic incorporation of predictor variables that encompass spatial and geodynamic ore controls information. The proposed 3D prospectivity modeling has successfully identified four gold targets in the Xiadian district. Among these targets, the depth of Jiangjiayao and Daobeizhuangzi orebodies exhibits the highest potential, likely indicating the presence of ore branching. Additionally, the No. 7 orebody at depth is anticipated to potentially host concealed gold mineralization.  
While the 3D prospectivity modeling approach is promising to be applied in the mineral exploration of various deposits, it is still limited in the aspects that (1) there is no geochemical and geophysical data directly related to deep possible mineralization as prediction variables, and (2) the ore-forming simulation validation can be further improved to decrease the uncertainty and bias, like [86; 87; 88]. In the future, we will (1) contact the Xiadian gold mine to verify these targets by drillholes, (2) integrate the geochemical and geophysical variables into the prospectivity modeling using the Bayesian decomposition model and deep learning techniques, and (3) develop an automatic optimization method for ore-forming simulations to enhance result reliability.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app131810277/s1](https://www.mdpi.com/article/10.3390/app131810277/s1)]([https://www.mdpi.com/article/10.3390/app131810277/s1](https://www.mdpi.com/article/10.3390/app131810277/s1)), Table S1: The detailed coordinates of controls point for gold targets at Xiadian.  
Conceptualization, Z.L. and J.W.; methodology, Z.L., J.W., W.S. and H.Z.; software, W.S. and Z.G.; investigation, Z.L. and Y.C.; resources, R.W.; data curation, R.W. and J.C.; writing--original draft preparation, Z.L., Z.G. and J.W.; writing--review and editing, R.W., H.D. and X.M.; supervision, J.C. and X.M.; project administration, Z.L. and X.M. All authors have read and agreed to the published version of the manuscript.  
This study was supported by projects of National Natural Science Foundation of China (42030809 and 42202332), Natural Science Foundation of Hunan Province (2023J\(\mid\)40715), and the science and technology innovation Program of Hunan Province (2021 RC4055).  
Not applicable.  
The authors do not have permission to share data.  
[PERSON], [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] are thanked for their assistance during field work.  
The authors declare no conflict of interest.