Code for "Unexplored Antarctic meteorite collection sites revealed through machine learning"
Creators
- 1. Laboratoire de Glaciologie, Université libre de Bruxelles, Brussels, Belgium.
- 2. Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, The Netherlands. Laboratoire de Glaciologie, Université libre de Bruxelles, Brussels, Belgium.
- 3. Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, The Netherlands.
- 4. Pattern Recognition Laboratory, Delft University of Technology, Delft, The Netherlands.
- 5. Laboratoire G-Time, Université libre de Bruxelles, Brussels, Belgium.
- 6. Analytical‐, Environmental‐, and Geo‐Chemistry, Vrije Universiteit Brussel, Brussels, Belgium.
Description
This archive provides scripts related to the following publication:
V. Tollenaar, H. Zekollari, S. Lhermitte, D. Tax, V. Debaille, S. Goderis, P. Claeys, F. Pattyn, Unexplored Antarctic meteorite collection sites revealed through machine learning. Science Advances 8, eabj8138 (2022). DOI: 10.1126/sciadv.abj8138
Contact: Veronica Tollenaar, Veronica.Tollenaar@ulb.be
Users should cite the original publication when using all or part of the code.
About the scripts: it includes the code to generate all results presented in the corresponding publication, as well an additional, user-oriented variant of the code that allows to directly classify a defined set of positive and unlabeled data as positive and negative observations. Further information is provided in the README.md file. Datasets needed to perform the analyses are provided at https://zenodo.org/record/5749752, or at external locations indicated in the references section of the publication.
Files
VeronicaTollenaar/AntarcticMeteorites-1.0.zip
Files
(245.8 kB)
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md5:68f7bafe8aecd012b542d6b778ce32f8
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Additional details
Related works
- Is supplement to
- https://github.com/VeronicaTollenaar/AntarcticMeteorites/tree/1.0 (URL)