Thesis
Experimental and machine learning tools to constrain pre-eruptive magmatic conditions and volcanoes with the potential for large-magnitude eruptions
- Abstract:
-
This thesis aims to develop new or refined petrological tools (i.e., thermometry, barometry, and hygrometry) using plagioclase feldspars, with a secondary aim of exploring the factors (i.e., eruptive records, subduction zone characteristics, geochemistry, edifice morphology) that contribute to the generation of large-magnitude eruptions (M≥6).
Expand abstract
Using random forest machine learning and a large compilation of plagioclase-bearing experimental petrology data (n = 1,152), new melt thermomete...
Actions
Access Document
- Files:
-
-
(Preview, Dissemination version, pdf, 22.9MB, Terms of use)
-
(Supplementary materials, zip, 1.1MB, Terms of use)
-
Authors
Contributors
+ Cassidy, M
- Institution:
- University of Birmingham
- Role:
- Supervisor
+ Blundy, J
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Earth Sciences
- Role:
- Supervisor
+ Mather, T
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Earth Sciences
- Role:
- Examiner
- ORCID:
- 0000-0003-4259-7303
+ Ferguson, D
- Role:
- Examiner
+ Natural Environment Research Council
More from this funder
- Funder identifier:
- https://ror.org/02b5d8509
- Funding agency for:
- Cutler, KS
- Grant:
- NE/S007474/1
- DOI:
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- University of Oxford
- Language:
-
English
- Keywords:
- Subjects:
- Pubs id:
-
2420760
- Local pid:
-
pubs:2420760
- Deposit date:
-
2026-05-03
- ARK identifier:
Terms of use
- Copyright holder:
- Kyra S. Cutler
- Copyright date:
- 2025
- Notes:
- Plagioclase-saturated melt hygrothermobarometry and plagioclase-melt equilibria using machine learning is derived from this thesis.
If you are the owner of this record, you can report an update to it here: Report update to this record