Published November 19, 2021
| Version v1
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Machine Learning Mid-Infrared Spectral Models for Predicting Modal Mineralogy of CI/CM Chondritic Asteroids and Bennu
Authors/Creators
- 1. Stony Brook University
- 2. Southwest Research Institute
- 3. Arizona State University
- 4. University of Arizona
- 5. American Museum of Natural History, Lamont Doherty Earth Observatory of Columbia University
- 6. Kingsborough Community College of the City University of New York
- 7. Purdue University
- 8. SUNY Oswego
Description
This is supporting data for the paper titled "Machine Learning Mid-Infrared Spectral Models for Predicting Modal Mineralogy of CI/CM Chondritic Asteroids and Bennu". Figure S1 compares model performance of nonnegative LSMA and PLS from Pan et al. (2015). Tables S1 through S5 provide XRD data, metadata, MIR spectra using the laboratory conversion, MIR spectra using the OTES conversion and quantitative XRD results for Murchison meteorite.
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