October 21, 2021 Dataset Open Access

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

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  <identifier identifierType="DOI">10.14278/rodare.1220</identifier>
  <creators>
    <creator>
      <creatorName>Schoenig, Jan</creatorName>
      <givenName>Jan</givenName>
      <familyName>Schoenig</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-9296-7582</nameIdentifier>
      <affiliation>Geoscience Centre Göttingen, University of Göttingen, Goldschmidtstraße 3, 37077 Göttingen, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>von Eynatten, Hilmar</creatorName>
      <givenName>Hilmar</givenName>
      <familyName>von Eynatten</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-2823-3194</nameIdentifier>
      <affiliation>Geoscience Centre Göttingen, University of Göttingen, Goldschmidtstraße 3, 37077 Göttingen, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Tolosana-Delgado, Raimon</creatorName>
      <givenName>Raimon</givenName>
      <familyName>Tolosana-Delgado</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-9847-0462</nameIdentifier>
      <affiliation>Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resources Technology, Chemnitzer Straße 40, 09599 Freiberg, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Meinhold, Guido</creatorName>
      <givenName>Guido</givenName>
      <familyName>Meinhold</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-8375-8375</nameIdentifier>
      <affiliation>Geoscience Centre Göttingen, University of Göttingen, Goldschmidtstraße 3, 37077 Göttingen, Germany; School of Geography, Geology and the Environment, Keele University, Keele, Staffordshire, ST5 5BG, UK; Institute for Geology, TU Bergakademie Freiberg, Bernhard-von-Cotta-Straße 2, 09599 Freiberg, Germany</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Garnet major-element composition as an indicator of host-rock type: a machine learning approach using the random forest classifier / supplementary data</title>
  </titles>
  <publisher>Rodare</publisher>
  <publicationYear>2021</publicationYear>
  <subjects>
    <subject>garnet major-element composition</subject>
    <subject>host-rock discrimination</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2021-10-21</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://rodare.hzdr.de/record/1220</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsPartOf">10.1007/s00410-021-01854-w</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://www.hzdr.de/publications/Publ-33278</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://static-content.springer.com/esm/art%3A10.1007%2Fs00410-021-01854-w/MediaObjects/410_2021_1854_MOESM1_ESM.xlsx</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.14278/rodare.1219</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/rodare</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The database includes 13615 garnet compositions of eight oxides commonly analysed in lab routines: SiO&lt;sub&gt;2&lt;/sub&gt;, TiO&lt;sub&gt;2&lt;/sub&gt;, Al&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;3&lt;/sub&gt;, Cr&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;3&lt;/sub&gt;, FeO&lt;sub&gt;total&lt;/sub&gt;, MnO, MgO, and CaO (in wt%). These are complemented by the following covariables:&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;setting and metamorphic facies class&lt;/strong&gt;: code indicating the geologic/tectonic setting of the host rock&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;composition class&lt;/strong&gt;: code indicating the compositional class of the host rock&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;author&lt;/strong&gt;: authors of the original paper providing the data&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;journal&lt;/strong&gt;: journal of the original paper&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;region&lt;/strong&gt;: origin of the data, in the format &amp;quot;region, country&amp;quot;&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;sample name&lt;/strong&gt;: sample ID in the original paper&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Pavg(kbar)&lt;/strong&gt;: if available, indicated pressure&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Tavg(&amp;deg;C)&lt;/strong&gt;: if available, indicated temperature&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;host-rock type and/or metamorphic facies&lt;/strong&gt;: facies indication of host rock&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;lithology and/or protolith&lt;/strong&gt;: composition indication of host rock&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;SiO2&lt;/strong&gt;: wt%&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;TiO2&lt;/strong&gt;: wt%&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Al2O3&lt;/strong&gt;: wt%&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Cr2O3&lt;/strong&gt;: wt%&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;FeOtotal&lt;/strong&gt;: wt%&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;MnO&lt;/strong&gt;: wt%&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;MgO&lt;/strong&gt;: wt%&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;CaO&lt;/strong&gt;: wt%&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&lt;/p&gt;

&lt;p&gt;This research was funded by DFG grant EY 23/27-1.&lt;/p&gt;</description>
    <description descriptionType="Other">{"references": ["Sch\u00f6nig, 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"]}</description>
  </descriptions>
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