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Machine learning for neuroimaging with scikit-learn

Overview of attention for article published in Frontiers in Neuroinformatics, January 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#19 of 850)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

twitter
76 X users
googleplus
1 Google+ user

Citations

dimensions_citation
1662 Dimensions

Readers on

mendeley
1296 Mendeley
citeulike
3 CiteULike
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Title
Machine learning for neuroimaging with scikit-learn
Published in
Frontiers in Neuroinformatics, January 2014
DOI 10.3389/fninf.2014.00014
Pubmed ID
Authors

Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux

X Demographics

X Demographics

The data shown below were collected from the profiles of 76 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 1,296 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 <1%
France 6 <1%
Germany 5 <1%
Canada 5 <1%
Brazil 5 <1%
United Kingdom 3 <1%
Netherlands 1 <1%
Israel 1 <1%
Finland 1 <1%
Other 5 <1%
Unknown 1256 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 256 20%
Researcher 176 14%
Student > Master 164 13%
Student > Bachelor 102 8%
Student > Doctoral Student 66 5%
Other 154 12%
Unknown 378 29%
Readers by discipline Count As %
Neuroscience 227 18%
Psychology 134 10%
Computer Science 134 10%
Engineering 112 9%
Medicine and Dentistry 62 5%
Other 178 14%
Unknown 449 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 48. 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 04 October 2023.
All research outputs
#909,745
of 26,146,017 outputs
Outputs from Frontiers in Neuroinformatics
#19
of 850 outputs
Outputs of similar age
#9,381
of 322,808 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#1
of 22 outputs
Altmetric has tracked 26,146,017 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 850 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. 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 322,808 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 97% of its contemporaries.
We're also able to compare this research output to 22 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 95% of its contemporaries.