Scientific article

English

A Machine Learning‐Based Approach to Clinopyroxene Thermobarometry: Model Optimization and Distribution for Use in Earth Sciences

ContributorsJorgenson, Corin Christen

; Higgins, Oliver John

; Begue, Florence; Caricchi, Luca

Published inJournal of geophysical research. Solid earth, vol. 127, no. 4

Publication date2022-04-09

First online date2022-04-09

Keywords

Clinopyroxene thermobarometry
Machine learning random forest
Model optimization

Affiliation entities

Faculté des sciences / Section des sciences de la Terre et de l'Environnement / Département des sciences de la Terre

Funding

European Commission - Forecasting the recurrence rate of volcanic eruptions [677493]
Swiss National Science Foundation - Quantifying the thermo-chemical evolution of magma reservoirs using mineral chemistry: a combined experimental and statistical approach [184632]
Università degli Stu - “ENGAGE” FRB-2019

Citation (ISO format)

JORGENSON, Corin Christen et al. A Machine Learning‐Based Approach to Clinopyroxene Thermobarometry: Model Optimization and Distribution for Use in Earth Sciences. In: Journal of geophysical research. Solid earth, 2022, vol. 127, n° 4. doi: 10.1029/2021JB022904

Article (Published version)

Identifiers

PID : unige:168082
DOI : 10.1029/2021JB022904
PMID : 35860374
PMCID : PMC9285709

Additional URL for this publicationhttps://onlinelibrary.wiley.com/doi/10.1029/2021JB022904

Journal ISSN2169-9313

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