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Genetic discrimination and mineralization analysis of rutile in the Xiadian Gold Deposit using machine learning

  • English Author:
  • Wang Rongchao¹, Yang Xiaoqi¹, Yang Xiaopeng¹, Gao Teng¹, Tang Weiyang¹, Chen Shujie¹, Chen Yudong²

  • Unit:
  • (1. Zhaojin Mining Industry Co., Ltd.; 2. School of Geosciences and Info‑physics, Central South University)
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Abstract:

Rutile is a common accessory mineral in the Jiaodong gold deposits, yet its genetie significance and metallogenic implications remain poorly constrained. This study integrates petrography, in-situ geochemical  analysis, and machine learning to investigate rutile from the Xiadian Gold Deposit at the southern end of the Zhaoping fault. Results reveal that rutile of the Xiadian Gold Deposit primarily occurs in silicified and sericitized alteration rocks beneath the Zhaoping fault, exhibiting cataclastic-metasomatic textures and coexisting with ore minerals such as pyriteand chalcopyrite. By compiling a global dataset of rutile from perse genetic and deposit types, a random forest model was applied to discriminate the origin of rutile based on its trace element characteristics in the Xiadian Gold Deposit. The model identifies the rutile of the Xiadian Gold Deposit as typical hydrothermal in origin, closely linked to gold mineralization. Furthermore, the rutile is classified as "Jiaodong-type"gold deposit genesis with high true-class rates indicating distinct trace element signatures compared to other deposit types. Among them, Cr, Si, W, Fe, Cu, V, and Ta are the elements that play important roles in discrimination. Enrichment of these elements suggests elemental mobilization from high-grade metamorphic basement rocks during mineralization and highlights the critical role of intense water-rock interactions in the formation of the Xiadian Gold Deposit.

Keywords:

rutile; elemental geochemistry; machine learning; genetic discrimination; Xiadian Gold Deposit; Zhao⁃ ping fault