https://youtu.be/nid2hVkEefE

The document discusses how machine learning can be used to predict unknown elemental concentrations from legacy geochemical data, aiding in the modernization and repurposing of older data for prospectivity mapping and exploration prioritization. The study demonstrates that predictive data generation through machine learning can enhance exploration programs by providing probable data in advance, helping to extract additional value from outdated data, assist in upstream data generation, and provide valuable information for downstream data usage. The method allows for the prediction of unanalyzed elements, reducing latency in utilizing modern data and potentially leading to targeted resource discoveries and increased probability of detecting geochemical anomalies. Read the full article here- https://shorturl.at/enQR6 P. Geo. Ricardo A Valls, M. Sc. and Geo Gadfly Valls Geoconsultant ORCID ID- https://orcid.org/0000-0002-5421-0914 Scopus Author ID: 7003369619/35335510700 ResearcherID: S-6604-2018 If you like this content, please "buy me a coffee" https://www.buymeacoffee.com/goldendroplets