Abstract Long-wave infrared (LWIR) spectra can be interpreted using a Random Forest machine learning approach to predict mineral species and abundances. In this study, hydrothermally altered carbonate rock core samples from the Fourmile Carlin-type Au discovery, Nevada, were analyzed by LWIR micro-X-ray fluorescence (μXRF). Linear programming-derived abundances quantified μXRF data used as trai...
