2023
DOI: 10.1002/gdj3.190
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A data screening approach to confirming a target mineral is chlorite using EPMA and LA‐ICPMS data

N. Freij,
D. D. Gregory,
Y. Liu

Abstract: Applying machine learning techniques to large datasets of in situ analyses has been proven to be a powerful tool in Earth Sciences. However, problems may arise when dealing with minerals such as chlorite, that exist as a solid solution rather than a single, stoichiometric ideal. It can be difficult to determine whether the variations in major element concentrations are due to compositional difference in the mineral of interest or due to sampling of the surrounding mineral phases in addition to the mineral of i… Show more

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Cited by 1 publication
(2 citation statements)
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“…Chlorite chemistry data was acquired from literature research, ScienceDirect, and GeoScienceWorld. Analyses went through extensive filtering to ensure that they can be confidently considered as chlorite (Freij et al, 2023). After these data were processed and filtered, 1,679 analyses remained from five papers studying five distinct areas: porphyry Cu-Au deposits in the Northparkes District in Australia (Pacey et al, 2020) and the Batu Hijau district in Indonesia (Wilkinson et al, 2015), Cu-Mo deposits in the Superior district of Arizona (Cooke et al, 2020) and El Teniente in Chile (Wilkinson et al, 2020), and a Cu-Mo-W deposit in Tongshankou, China (Chu et al, 2020).…”
Section: Data Sourcementioning
confidence: 99%
See 1 more Smart Citation
“…Chlorite chemistry data was acquired from literature research, ScienceDirect, and GeoScienceWorld. Analyses went through extensive filtering to ensure that they can be confidently considered as chlorite (Freij et al, 2023). After these data were processed and filtered, 1,679 analyses remained from five papers studying five distinct areas: porphyry Cu-Au deposits in the Northparkes District in Australia (Pacey et al, 2020) and the Batu Hijau district in Indonesia (Wilkinson et al, 2015), Cu-Mo deposits in the Superior district of Arizona (Cooke et al, 2020) and El Teniente in Chile (Wilkinson et al, 2020), and a Cu-Mo-W deposit in Tongshankou, China (Chu et al, 2020).…”
Section: Data Sourcementioning
confidence: 99%
“…Data was filtered after the methods of Freij et al (2023), and a summary of the process is provided here. The first step in processing the data was to determine whether the data acquired from literature sources was chemically consistent with chlorite.…”
Section: Data Processingmentioning
confidence: 99%