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Inferring epidemiological parameters from phylogenies using regression-ABC: A comparative study

Overview of attention for article published in PLoS Computational Biology, March 2017
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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 (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
13 X users
reddit
1 Redditor

Readers on

mendeley
80 Mendeley
citeulike
1 CiteULike
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Article details
Title
Inferring epidemiological parameters from phylogenies using regression-ABC: A comparative study
Published in
PLoS Computational Biology, March 2017
DOI 10.1371/journal.pcbi.1005416
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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Activity
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X Demographics

X Demographics

The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 1%
Unknown 79 99%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 23 29%
Student > Ph. D. Student 16 20%
Student > Master 8 10%
Professor > Associate Professor 4 5%
Student > Bachelor 3 4%
Other 9 11%
Unknown 17 21%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 13 16%
Medicine and Dentistry 9 11%
Mathematics 6 8%
Computer Science 5 6%
Biochemistry, Genetics and Molecular Biology 4 5%
Other 20 25%
Unknown 23 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 30 June 2025.
All research outputs
#1,771,183
of 34,411,289 outputs
Outputs from PLoS Computational Biology
#1,187
of 10,418 outputs
Outputs of similar age
#26,153
of 353,183 outputs
Outputs of similar age from PLoS Computational Biology
#38
of 162 outputs
Altmetric has tracked 34,411,289 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,418 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.8. This one has done well, scoring higher than 88% 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 353,183 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 162 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.