Advancing censored geochemical Au prediction through Bayesian spatial models and Random Forest with fractal-based background separation
Crossref DOI link: https://doi.org/10.1038/s41598-026-34999-4
Published Online: 2026-01-06
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Mahdiyanfar, Hossein
Text and Data Mining valid from 2026-01-06
Version of Record valid from 2026-02-04
Article History
Received: 2 October 2025
Accepted: 1 January 2026
First Online: 6 January 2026
Declarations
:
: The authors declare no competing interests.