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

  • Pablo Martínez-Sosa (Contributor)
  • Jessica E Tierney (Contributor)
  • Lina C. Pérez-Angel (Contributor)
  • Ioana C. Stefanescu (Contributor)
  • Frédérique M.S.A. Kirkels (Contributor)
  • Francien Peterse (Contributor)
  • Bryan Shuman (Contributor)

Dataset

Description

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(km), Mean Annual Air Temperature (C), and pH-, as well as fractional abundance of isoprenoid and branched GDGTs for unpublished samples used for the training of the Branched and Isoprenoid GDGT Machine learning Classification (BIGMaC) algorithm (Martínes-Sosa, et al., in prep).
Date made availableJan 10 2023
PublisherZENODO

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