Autonomous data extraction from peer reviewed literature for training machine learning models of oxidation potentials

Autonomous data extraction from peer reviewed literature for training machine learning models of oxidation potentials

We present an automated data-collection pipeline involving a convolutional neural network and a large language model to extract user-specified tabular data from peer-reviewed literature. The pipeline is applied to 74 reports published between 1957 and 2014 with experimentally-measured oxidation pote...

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Bibliographic Details
Main Authors: Siwoo Lee, Stefan Heinen, Danish Khan, O Anatole von Lilienfeld
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Machine Learning: Science and Technology
Subjects:
quantum chemistry
machine learning
oxidation potentials
large language model
literature data extraction
Online Access:https://doi.org/10.1088/2632-2153/ad2f52

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