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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identifying Vulnerable Brain Networks in Mouse Models of Genetic Risk Factors for Late Onset Alzheimer’s Disease
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, December 2019
|
| DOI | 10.3389/fninf.2019.00072 |
| Pubmed ID | |
| Authors |
Alexandra Badea, Wenlin Wu, Jordan Shuff, Michele Wang, Robert J. Anderson, Yi Qi, G. Allan Johnson, Joan G. Wilson, Serge Koudoro, Eleftherios Garyfallidis, Carol A. Colton, David B. Dunson |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 17% |
| Spain | 1 | 17% |
| United States | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 54 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 13% |
| Student > Ph. D. Student | 6 | 11% |
| Student > Master | 5 | 9% |
| Student > Bachelor | 4 | 7% |
| Student > Doctoral Student | 3 | 6% |
| Other | 10 | 19% |
| Unknown | 19 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 13 | 24% |
| Psychology | 4 | 7% |
| Medicine and Dentistry | 3 | 6% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Agricultural and Biological Sciences | 2 | 4% |
| Other | 5 | 9% |
| Unknown | 24 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 17 January 2020.
All research outputs
#2,722,633
of 25,563,770 outputs
Outputs from Frontiers in Neuroinformatics
#99
of 843 outputs
Outputs of similar age
#63,386
of 478,471 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#3
of 11 outputs
Altmetric has tracked 25,563,770 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 843 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has done well, scoring higher than 88% 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 478,471 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.