A review of machine learning in geochemistry and cosmochemistry: method improvements and applications

Y He, Y Zhou, T Wen, S Zhang, F Huang, X Zou… - Applied …, 2022 - Elsevier
The development of analytical and computational techniques and growing scientific funds
collectively contribute to the rapid accumulation of geoscience data. The massive amount of …

Correlating tephras and cryptotephras using glass compositional analyses and numerical and statistical methods: review and evaluation

DJ Lowe, NJG Pearce, MA Jorgensen… - Quaternary Science …, 2017 - Elsevier
We define tephras and cryptotephras and their components (mainly ash-sized particles of
glass±crystals in distal deposits) and summarize the basis of tephrochronology as a …

Machine learning thermo‐barometry: Application to clinopyroxene‐bearing magmas

M Petrelli, L Caricchi, D Perugini - Journal of Geophysical …, 2020 - Wiley Online Library
We introduce a new approach, based on machine learning, to estimate pre‐eruptive
temperatures and storage depths using clinopyroxene‐melt pairs and clinopyroxene‐only …

Apatite trace element composition as an indicator of ore deposit types: A machine learning approach

KF Qiu, T Zhou, D Chew, ZL Hou, A Müller… - American …, 2024 - degruyter.com
The diverse suite of trace elements incorporated into apatite in ore-forming systems has
important applications in petrogenesis studies of mineral deposits. Trace element variations …

A machine learning method for distinguishing detrital zircon provenance

SH Zhong, Y Liu, SZ Li, IN Bindeman… - … to Mineralogy and …, 2023 - Springer
Zircon geochemistry provides a sensitive monitor of its parental magma composition.
However, due to the complexity of the uptake of trace elements during zircon growth …

Artifact3-D: New software for accurate, objective and efficient 3D analysis and documentation of archaeological artifacts

L Grosman, A Muller, I Dag, H Goldgeier, O Harush… - PLoS …, 2022 - journals.plos.org
The study of artifacts is fundamental to archaeological research. The features of individual
artifacts are recorded, analyzed, and compared within and between contextual …

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

J Schönig, H von Eynatten… - … to Mineralogy and …, 2021 - Springer
The major-element chemical composition of garnet provides valuable petrogenetic
information, particularly in metamorphic rocks. When facing detrital garnet, information about …

Statistical features for land use and land cover classification in Google Earth Engine

WR Becker, TB Ló, JA Johann, E Mercante - Remote Sensing Applications …, 2021 - Elsevier
The possibility of identifying and quantifying agricultural areas objectively and quickly is a
relevant aspect in the Brazilian agricultural context, given the territorial extent of the country …

Weka trainable segmentation plugin in ImageJ: a semi-automatic tool applied to crystal size distributions of microlites in volcanic rocks

C Lormand, GF Zellmer, K Németh… - Microscopy and …, 2018 - academic.oup.com
Crystals within volcanic rocks record geochemical and textural signatures during magmatic
evolution before eruption. Clues to this magmatic history can be examined using crystal size …

Advancing tephrochronology as a global dating tool: applications in volcanology, archaeology, and palaeoclimatic research

CS Lane, DJ Lowe, SPE Blockley, T Suzuki… - Quaternary …, 2017 - Elsevier
Layers of far-travelled volcanic ash (tephra) from explosive volcanic eruptions provide
stratigraphic and numerical dating horizons in sedimentary and volcanic sequences. Such …