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Identification of hypoglycemia-specific neural signals by decoding murine vagus nerve activity

Overview of attention for article published in Bioelectronic Medicine, July 2019
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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 (98th percentile)

Mentioned by

news
17 news outlets
twitter
4 tweeters

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
17 Mendeley
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Title
Identification of hypoglycemia-specific neural signals by decoding murine vagus nerve activity
Published in
Bioelectronic Medicine, July 2019
DOI 10.1186/s42234-019-0025-z
Authors

Emily Battinelli Masi, Todd Levy, Tea Tsaava, Chad E. Bouton, Kevin J. Tracey, Sangeeta S. Chavan, Theodoros P. Zanos

Twitter Demographics

The data shown below were collected from the profiles of 4 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 24%
Student > Ph. D. Student 4 24%
Student > Bachelor 3 18%
Professor 1 6%
Unknown 5 29%
Readers by discipline Count As %
Engineering 6 35%
Neuroscience 2 12%
Medicine and Dentistry 1 6%
Earth and Planetary Sciences 1 6%
Chemistry 1 6%
Other 1 6%
Unknown 5 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 132. 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 09 July 2020.
All research outputs
#146,710
of 15,457,193 outputs
Outputs from Bioelectronic Medicine
#3
of 48 outputs
Outputs of similar age
#4,142
of 262,088 outputs
Outputs of similar age from Bioelectronic Medicine
#1
of 1 outputs
Altmetric has tracked 15,457,193 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 48 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.9. This one scored the same or higher as 45 of them.
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 262,088 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 98% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them