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Best practices for replicability, reproducibility and reusability of computer-based experiments exemplified by model reduction software

Overview of attention for article published in arXiv, January 2016
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

twitter
20 tweeters
wikipedia
1 Wikipedia page
googleplus
2 Google+ users

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
34 Mendeley
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Title
Best practices for replicability, reproducibility and reusability of computer-based experiments exemplified by model reduction software
Published in
arXiv, January 2016
DOI 10.3934/math.2016.3.261
Authors

Jörg Fehr, Jan Heiland, Christian Himpe, Jens Saak

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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 38%
Student > Master 6 18%
Researcher 3 9%
Other 2 6%
Student > Doctoral Student 2 6%
Other 3 9%
Unknown 5 15%
Readers by discipline Count As %
Computer Science 9 26%
Mathematics 5 15%
Engineering 4 12%
Biochemistry, Genetics and Molecular Biology 3 9%
Energy 2 6%
Other 5 15%
Unknown 6 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 18 May 2021.
All research outputs
#1,221,754
of 17,864,600 outputs
Outputs from arXiv
#19,682
of 717,162 outputs
Outputs of similar age
#24,692
of 267,984 outputs
Outputs of similar age from arXiv
#428
of 15,884 outputs
Altmetric has tracked 17,864,600 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 717,162 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 97% 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 267,984 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 90% of its contemporaries.
We're also able to compare this research output to 15,884 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.