Dataset Open Access

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.

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  • 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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Publication date:
October 21, 2021
DOI:
10.14278/rodare.1220

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Keyword(s):
garnet major-element composition host-rock discrimination
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