Exploring Effects of Modified Machine Learning Pipelines of Astrochemical Inventories

Machine learning pipelines for astrochemical inventories have been introduced as a useful addition to the astrochemist toolbox, having first been used to model and predict column densities in the Taurus Molecular Cloud (TMC-1). Rapid changes in the field of machine learning have provided new tools i...

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Bibliographic Details
Main Authors: Hannah Toru Shay, Haley N. Scolati, Gabi Wenzel, Kin Long Kelvin Lee, Aravindh N. Marimuthu, Brett A. McGuire
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astrophysical Journal
Subjects:
Online Access:https://doi.org/10.3847/1538-4357/adc80b
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