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A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model

Overview of attention for article published in BMC Bioinformatics, May 2008
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

twitter
20 tweeters

Citations

dimensions_citation
51 Dimensions

Readers on

mendeley
92 Mendeley
citeulike
3 CiteULike
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Title
A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model
Published in
BMC Bioinformatics, May 2008
DOI 10.1186/1471-2105-9-241
Pubmed ID
Authors

Richard Judson, Fathi Elloumi, R Woodrow Setzer, Zhen Li, Imran Shah

Twitter Demographics

The data shown below were collected from the profiles of 20 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Sweden 1 1%
Argentina 1 1%
Australia 1 1%
Unknown 87 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 27%
Researcher 18 20%
Student > Master 9 10%
Student > Bachelor 5 5%
Student > Doctoral Student 5 5%
Other 21 23%
Unknown 9 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 26%
Computer Science 17 18%
Chemistry 11 12%
Medicine and Dentistry 6 7%
Biochemistry, Genetics and Molecular Biology 6 7%
Other 14 15%
Unknown 14 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 15 December 2017.
All research outputs
#1,767,803
of 16,191,272 outputs
Outputs from BMC Bioinformatics
#633
of 5,862 outputs
Outputs of similar age
#45,473
of 296,154 outputs
Outputs of similar age from BMC Bioinformatics
#60
of 439 outputs
Altmetric has tracked 16,191,272 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,862 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 89% of its peers.
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 296,154 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 439 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.