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Using Machine Learning for Biosignature Detection with Pyrolysis Gas Chromatography-Mass Spectrometry Data

The software preprocesses pyrolysis gas chromatography-mass spectrometry data and applies machine learning to detect whether terrestrial and extraterrestrial carbonaceous materials are of biotic or abiotic origin. It then determines the patterns of "important variables" that distinguish abiotic from biotic species. The software is written in R.