## 4 Results and Discussion  
### Model and Feature Visualization  
The models show the gold orebodies in the Xiadian district are distributed unevenly, consisting of several Au enrichment segments, of which No. 7 is the largest gold orebody and others have a long-lensed feature (Figure 6(a)). The general dip of gold mineralization is weakly variable (\(\sim\)45\({}^{\circ}\)), but there is a notable increase in thickness at depths ranging from \(-\)500 m to \(-\)1300 m compared to the shallow and deep regions. Additionally, there are downward branches from the main gold zone at deep, displaying a gradual decrease in gold mineralization density. The statistics of Au grade of voxels, including drill holes, show the voxels of high Au grade (\(>\)4 g/t) occupy a small proportion and are distributed irregularly in the No. 5 and JJY orebodies. The majority of voxels exhibit low gold grades, ranging from 0 to 3 g/t (Figure 6(b)). The Zhaoping fault model entirety presents the fault spatial features in a 3D view, making it easier to understand the mineralization location association with the fault geometry. The models reveal that the Zhaoping fault has many local undulations that company variations in both dip and strike (Figure 6(c)). These geometric features play a significant role in controlling ore body formation, particularly evident in the segments of the deep No. 7 and the shallow DBZZ, where both orebodies pinch out, and substantial transitions in fault shape (Figure 6(c)). On a larger scale, the boundaries of No. 7 orebodies are often characterized by fault dip or strike variations, while the areas near the inner parts of the orebodies show inconspicuous changes in geometry. To better elucidate the complicated controls of fault geometry variation on mineralization, we present the orebody model with attributes of fault features and their quantitative correlation with gold mineralization (Figures 8 and 9). The results highlight the models with a heterogeneous distribution of the effects of fault features (Figure 8) and the correlation is nonlinear (Figure 9). The distance between ore and fault generally ranges from 50 to \(-\)300 m, with a majority falling within \(-\)200 to 0 m, consistent with the football distribution characteristics. Overall, the No. 7 including high ore-bearing units is situated closer to the fault than (No. 2, JJY and DBZZ; Figures 8a and 9a). Gold is widely distributed in the ranges of fault dip, but mostly in the dips from 30\({}^{\circ}\) to 60\({}^{\circ}\) (Figure 9b). The large fault dip occurs in the deep segments of JJY and DBZZ where ore branching occurs. The fault dip changes are generally variable near 0 with a SE-plunging distribution feature (Figures 8d and 9c). The high degree (>10\({}^{\circ}\)) of dip variation is all positive, reaching up to 40\({}^{\circ}\), which also influences the formation of high ore-bearing bodies. This means the fault from gentle to steep can promote the formation of high-grade ore, which supports the vein ore affinity to deep fractures. Notably, the locally consistent distribution of fault dip and orebodies (e.g., No. 7 center, JJY and DBZZ) well supports the model of fault geometry controls on gold (Figure 4). The presence of two scales of fault undulation reveals the main ore voxels are confined to areas with negative (convex parts; Figures 8e,f and 9d,e), with no presence of very large fault undulations, which aligns with gentle feature observed (Figure 7c). Overall, the geometric features of the Zhaoping fault aptly reflect the structural controls on gold pattern of ore-forming model (Figure 4). Thus, they can be selected as predictive variables for gold prospectivity modeling. Figure 7: 3D raster models of gold orebodies (**a**,**b**) and implicit model of the Zhaoping fault model (**c**). Note the fault model covers the peripheral areas of the Xiadian gold deposit. Note the orebody (transparent, grey areas) is located in the fault footwall.