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Improving functional magnetic resonance imaging reproducibility

Overview of attention for article published in Giga Science, March 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

blogs
1 blog
twitter
61 X users
peer_reviews
1 peer review site
facebook
4 Facebook pages
googleplus
2 Google+ users

Citations

dimensions_citation
38 Dimensions

Readers on

mendeley
97 Mendeley
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Title
Improving functional magnetic resonance imaging reproducibility
Published in
Giga Science, March 2015
DOI 10.1186/s13742-015-0055-8
Pubmed ID
Authors

Cyril Pernet, Jean-Baptiste Poline

Abstract

The ability to replicate an entire experiment is crucial to the scientific method. With the development of more and more complex paradigms, and the variety of analysis techniques available, fMRI studies are becoming harder to reproduce. In this article, we aim to provide practical advice to fMRI researchers not versed in computing, in order to make studies more reproducible. All of these steps require researchers to move towards a more open science, in which all aspects of the experimental method are documented and shared. Only by sharing experiments, data, metadata, derived data and analysis workflows will neuroimaging establish itself as a true data science.

X Demographics

X Demographics

The data shown below were collected from the profiles of 61 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 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 2%
United Kingdom 2 2%
Hong Kong 1 1%
Germany 1 1%
Greece 1 1%
United States 1 1%
Unknown 89 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 25%
Researcher 18 19%
Student > Master 14 14%
Student > Bachelor 9 9%
Professor > Associate Professor 8 8%
Other 19 20%
Unknown 5 5%
Readers by discipline Count As %
Psychology 26 27%
Computer Science 12 12%
Neuroscience 12 12%
Agricultural and Biological Sciences 10 10%
Medicine and Dentistry 8 8%
Other 17 18%
Unknown 12 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 46. 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 22 March 2021.
All research outputs
#917,863
of 25,584,565 outputs
Outputs from Giga Science
#120
of 1,174 outputs
Outputs of similar age
#11,331
of 279,737 outputs
Outputs of similar age from Giga Science
#3
of 18 outputs
Altmetric has tracked 25,584,565 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,174 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.7. 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 279,737 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 95% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.