a practical step toward data-driven, reproducible mineral exploration, supporting more efficient, scalable, and responsible resource discovery. ACKNOWLEDGEMENTS The authors sincerely thank the Directorate of Mineral and Energy Resources (DRME) of INGEMMET for providing the facilities and institutional support that made this research and participation possible. Special thanks are extended to Dr. Jorge Chira, Director of the DRME, and to Eng. Italo Rodríguez, team leader of the Systematization of Economic Geological Information (SIGE), for their crucial support in enabling enrollment and for their unwavering commitment to advancing this initiative. The authors also express their gratitude to Eng. Víctor Torres for guidance on prospecting-related alterations; to Eng. Luis Quispe for instruction in metallogeny; and to Eng. Juan Casas for technical support in ASTER image processing. The authors additionally acknowledge Martha Ly, ESG Mining Regional Leader and Earth & Environment Sector Leader for LAC at WSP Peru, and Dani Gutiérrez, Senior Environmental Specialist and Water Resources Leader at WSP Peru, for their institutional support and encouragement of digital innovation initiatives that contributed to the broader development and application of this work. REFERENCES 1. Abedini, M., Ziaii, M., Timkin, T., & Beiranvand Pour, A. (2023). Machine learning (ML)- based copper mineralization prospectivity mapping (MPM) using mining geochemistry method and remote sensing satellite data. Remote Sensing, 15(15), 3708. https://doi.org/10.3390/rs15153708 2. Avendaño, A., Walter, E., & Romero Fernández, D. (2000). Memoria descriptiva de la geología del cuadrángulo de Puquina 34-t (Escala 1:50 000). Instituto Geológico Minero y Metalúrgico (INGEMMET). 3. Balaram, V., & Sawant, S. S. (2022). Indicator minerals, pathfinder elements, and portable analytical instruments in mineral exploration studies. Minerals, 12(4), 394. https://doi.org/10.3390/min12040394 4. Barnett, R. M. (2017). Principal component analysis. In J. L. Deutsch (Ed.), Geostatistics lessons. 5. Bellido Bravo, E., & Guevara Rosillo, C. (1963). Geología de los cuadrángulos de Punta de Bombón y Clemesí (Hojas 35-s y 35-t) (Boletín A 5). Instituto Geológico Minero y Metalúrgico (INGEMMET). 6. Chen, S. (2015). Principal component analysis of geochemical data from the REE-rich maw
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