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1. Machine Learning Applications for Chemical Fingerprinting and Environmental Source Tracking Using Non-target Chemical Data

Author

Emmanuel Dávila-Santiago, Cheng Shi, Gouri Mahadwar, Bridgette Medeghini, Logan Insinga, Rebecca Hutchinson, Stephen Good, and Gerrad D. Jones

Subjects
Machine Learning, Livestock, Animals, Environmental Chemistry, Agriculture, General Chemistry, Wastewater, Environmental Monitoring
Abstract

A frequent goal of chemical forensic analyses is to select a panel of diagnostic chemical features─colloquially termed a chemical fingerprint─that can predict the presence of a source in a novel sample. However, most of the developed chemical fingerprinting workflows are qualitative in nature. Herein, we report on a quantitative machine learning workflow. Grab samples (

Published
2022
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