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X Demographics
Mendeley readers
Attention Score in Context
| 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 |
| Pubmed ID | |
| Authors |
Emily Battinelli Masi, Todd Levy, Tea Tsaava, Chad E. Bouton, Kevin J. Tracey, Sangeeta S. Chavan, Theodoros P. Zanos |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 60% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 40% |
| Members of the public | 2 | 40% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 23% |
| Researcher | 7 | 16% |
| Student > Bachelor | 4 | 9% |
| Student > Master | 3 | 7% |
| Professor | 2 | 5% |
| Other | 1 | 2% |
| Unknown | 17 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 9 | 20% |
| Neuroscience | 4 | 9% |
| Chemistry | 3 | 7% |
| Immunology and Microbiology | 2 | 5% |
| Medicine and Dentistry | 2 | 5% |
| Other | 5 | 11% |
| Unknown | 19 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 130. 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 29 March 2021.
All research outputs
#274,133
of 23,151,828 outputs
Outputs from Bioelectronic Medicine
#6
of 105 outputs
Outputs of similar age
#6,054
of 346,562 outputs
Outputs of similar age from Bioelectronic Medicine
#1
of 8 outputs
Altmetric has tracked 23,151,828 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 105 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.4. This one has done particularly well, scoring higher than 94% 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 346,562 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 8 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