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Garnet major-element composition as an indicator of host-rock type: a machine learning approach using the random forest classifier / supplementary data

Schoenig, Jan; von Eynatten, Hilmar; Tolosana-Delgado, Raimon; Meinhold, Guido

The database includes 13615 garnet compositions of eight oxides commonly analysed in lab routines: SiO2, TiO2, Al2O3, Cr2O3, FeOtotal, MnO, MgO, and CaO (in wt%). These are complemented by the following covariables:

setting and metamorphic facies class: code indicating the geologic/tectonic setting of the host rock

composition class: code indicating the compositional class of the host rock

author: authors of the original paper providing the data

journal: journal of the original paper

region: origin of the data, in the format "region, country"

sample name: sample ID in the original paper

Pavg(kbar): if available, indicated pressure

Tavg(°C): if available, indicated temperature

host-rock type and/or metamorphic facies: facies indication of host rock

lithology and/or protolith: composition indication of host rock

SiO2: wt%

TiO2: wt%

Al2O3: wt%

Cr2O3: wt%

FeOtotal: wt%

MnO: wt%

MgO: wt%

CaO: wt%

 

This research was funded by DFG grant EY 23/27-1.

Embargoed Access

Files are currently under embargo but will be publicly accessible after December 31, 2022.


Data will be accessible when the associated paper is finally published. Please cite the paper and not the data.


  • Schönig, J.; von Eynatten, H.; Tolosana-Delgado, R.; Meinhold, G. (in press) Garnet major-element composition as an indicator of host-rock type: a machine learning approach using the random forest classifier. Contributions to Mineralogy and Petrology; .doi: 10.1007/s00410-021-01854-w

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