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NNMT: Mean-Field Based Analysis Tools for Neuronal Network Models

Overview of attention for article published in Frontiers in Neuroinformatics, May 2022
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
5 Mendeley
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Title
NNMT: Mean-Field Based Analysis Tools for Neuronal Network Models
Published in
Frontiers in Neuroinformatics, May 2022
DOI 10.3389/fninf.2022.835657
Pubmed ID
Authors

Moritz Layer, Johanna Senk, Simon Essink, Alexander van Meegen, Hannah Bos, Moritz Helias

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Professor 1 20%
Student > Ph. D. Student 1 20%
Student > Doctoral Student 1 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 40%
Neuroscience 1 20%
Engineering 1 20%
Unknown 1 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 06 November 2023.
All research outputs
#15,760,397
of 24,954,788 outputs
Outputs from Frontiers in Neuroinformatics
#527
of 813 outputs
Outputs of similar age
#220,050
of 433,077 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#22
of 38 outputs
Altmetric has tracked 24,954,788 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 813 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
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 433,077 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.