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LSTMVoter: chemical named entity recognition using a conglomerate of sequence labeling tools

Overview of attention for article published in Journal of Cheminformatics, January 2019
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
4 X users

Citations

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27 Dimensions

Readers on

mendeley
54 Mendeley
Title
LSTMVoter: chemical named entity recognition using a conglomerate of sequence labeling tools
Published in
Journal of Cheminformatics, January 2019
DOI 10.1186/s13321-018-0327-2
Pubmed ID
Authors

Wahed Hemati, Alexander Mehler

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 17%
Researcher 9 17%
Student > Bachelor 6 11%
Professor > Associate Professor 4 7%
Student > Master 4 7%
Other 8 15%
Unknown 14 26%
Readers by discipline Count As %
Computer Science 21 39%
Business, Management and Accounting 5 9%
Agricultural and Biological Sciences 3 6%
Linguistics 2 4%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 8 15%
Unknown 14 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 January 2019.
All research outputs
#14,909,862
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#743
of 891 outputs
Outputs of similar age
#237,005
of 445,537 outputs
Outputs of similar age from Journal of Cheminformatics
#28
of 28 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 445,537 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.