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ABC random forests for Bayesian parameter inference

Overview of attention for article published in Bioinformatics, October 2018
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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

blogs
1 blog
policy
1 policy source
twitter
5 X users

Readers on

mendeley
245 Mendeley
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Article details
Title
ABC random forests for Bayesian parameter inference
Published in
Bioinformatics, October 2018
DOI 10.1093/bioinformatics/bty867
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 5 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 245 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 2 <1%
United Kingdom 2 <1%
Germany 1 <1%
Unknown 240 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 49 20%
Student > Ph. D. Student 46 19%
Student > Master 29 12%
Student > Bachelor 17 7%
Other 10 4%
Other 35 14%
Unknown 59 24%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 69 28%
Biochemistry, Genetics and Molecular Biology 28 11%
Mathematics 24 10%
Computer Science 21 9%
Environmental Science 9 4%
Other 26 11%
Unknown 68 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 01 January 2023.
All research outputs
#3,097,285
of 28,812,439 outputs
Outputs from Bioinformatics
#2,155
of 13,306 outputs
Outputs of similar age
#55,215
of 365,360 outputs
Outputs of similar age from Bioinformatics
#35
of 251 outputs
Altmetric has tracked 28,812,439 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 13,306 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 83% 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 365,360 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 251 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.