ChemDataExtractor specifications

Information


Unique identifier OMICS_15623
Name ChemDataExtractor
Software type Toolkit/Suite
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages Python
License MIT License
Computer skills Advanced
Version 1.3.0
Stability Stable
Maintained Yes

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Versioning


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Documentation


Maintainer


  • person_outline Jacqueline Cole

Publication for ChemDataExtractor

ChemDataExtractor citation

library_books

Machine learned and codified synthesis parameters of oxide materials

2017
Sci Data
PMCID: 5595045
PMID: 28895943
DOI: 10.1038/sdata.2017.127

[…] seline: the categorical accuracy of this neural network classifier, as measured against the same test set, is 86% and its F1 score is 81%. This is comparable to the performance achieved by the recent ChemDataExtractor model on a similar task, which is trained to extract relevant text from chemistry articles. shows the process of interpreting higher-level relations in the text, including resolving […]

ChemDataExtractor institution(s)
Cavendish Laboratory, University of Cambridge, Cambridge, UK
ChemDataExtractor funding source(s)
This work was supported by the EPSRC for a DTA PhD studentship (Grant No. EP/J500380/1) and the 1851 Royal Commission for the 2014 Design Fellowship.

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