Detailed Record



Environmental data and fractional abundance of iso and branched GDGT data used to train the BIGMaC algorithm


Abstract Location, environmental data -depth (m), elevation, distance to land (km), Mean Annual Air Temperature (C), and pH-, as well as fractional abundance of isoprenoid and branched GDGTs for unpublished samples used for the training of the Branched and Isoprenoid GDGT Machine learning Classification (BIGMaC) algorithm.
Authors Pablo Martínez‐Sosa ORCID , Jessica E. Tierney ORCID , Lina C. Pérez‐Angel ORCID , Ioana C. Stefanescu University of WyomingORCID , Jingjing Guo ORCID , Frédérique Kirkels ORCID , Julio Sepúlveda ORCID , Francien Peterse ORCID , Bryan N. Shuman University of WyomingORCID , Alberto V. Reyes ORCID
Journal Info European Organization for Nuclear Research | Zenodo
Publication Date 1/10/2023
ISSN Not listed
TypeKeyword Image dataset
Open Access gold Gold Access
DOI https://doi.org/10.5281/zenodo.7522414
KeywordsKeyword Image