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X Demographics
Mendeley readers
Attention Score in Context
| Title |
High-throughput proteomics fiber typing (ProFiT) for comprehensive characterization of single skeletal muscle fibers
|
|---|---|
| Published in |
Skeletal Muscle, March 2020
|
| DOI | 10.1186/s13395-020-00226-5 |
| Pubmed ID | |
| Authors |
Sebastian Kallabis, Lena Abraham, Stefan Müller, Verena Dzialas, Clara Türk, Janica Lea Wiederstein, Theresa Bock, Hendrik Nolte, Leonardo Nogara, Bert Blaauw, Thomas Braun, Marcus Krüger |
X Demographics
The data shown below were collected from the profiles of 16 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 | 4 | 25% |
| United Kingdom | 1 | 6% |
| Chile | 1 | 6% |
| Denmark | 1 | 6% |
| Japan | 1 | 6% |
| Canada | 1 | 6% |
| Australia | 1 | 6% |
| Unknown | 6 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 8 | 50% |
| Members of the public | 7 | 44% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 27% |
| Researcher | 5 | 14% |
| Student > Bachelor | 4 | 11% |
| Professor | 3 | 8% |
| Other | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 11 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 11 | 30% |
| Medicine and Dentistry | 2 | 5% |
| Neuroscience | 2 | 5% |
| Social Sciences | 2 | 5% |
| Business, Management and Accounting | 1 | 3% |
| Other | 6 | 16% |
| Unknown | 13 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 13 April 2020.
All research outputs
#3,790,729
of 25,837,817 outputs
Outputs from Skeletal Muscle
#88
of 394 outputs
Outputs of similar age
#85,050
of 394,256 outputs
Outputs of similar age from Skeletal Muscle
#4
of 11 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 394 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has done well, scoring higher than 77% 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 394,256 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 78% 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 gotten more attention than average, scoring higher than 63% of its contemporaries.