Title |
Open-CSAM, a new tool for semi-automated analysis of myofiber cross-sectional area in regenerating adult skeletal muscle
|
---|---|
Published in |
Skeletal Muscle, January 2019
|
DOI | 10.1186/s13395-018-0186-6 |
Pubmed ID | |
Authors |
Thibaut Desgeorges, Sophie Liot, Solene Lyon, Jessica Bouvière, Alix Kemmel, Aurélie Trignol, David Rousseau, Bruno Chapuis, Julien Gondin, Rémi Mounier, Bénédicte Chazaud, Gaëtan Juban |
X Demographics
The data shown below were collected from the profiles of 57 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 11 | 19% |
United States | 6 | 11% |
Australia | 6 | 11% |
Canada | 5 | 9% |
Denmark | 2 | 4% |
Sweden | 1 | 2% |
Thailand | 1 | 2% |
Austria | 1 | 2% |
Italy | 1 | 2% |
Other | 8 | 14% |
Unknown | 15 | 26% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 39 | 68% |
Scientists | 17 | 30% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 74 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 15 | 20% |
Researcher | 14 | 19% |
Student > Bachelor | 10 | 14% |
Student > Master | 5 | 7% |
Professor > Associate Professor | 3 | 4% |
Other | 9 | 12% |
Unknown | 18 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 25 | 34% |
Agricultural and Biological Sciences | 8 | 11% |
Sports and Recreations | 4 | 5% |
Medicine and Dentistry | 3 | 4% |
Engineering | 3 | 4% |
Other | 6 | 8% |
Unknown | 25 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 36. 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 June 2022.
All research outputs
#1,037,635
of 23,979,951 outputs
Outputs from Skeletal Muscle
#8
of 372 outputs
Outputs of similar age
#25,455
of 444,439 outputs
Outputs of similar age from Skeletal Muscle
#1
of 7 outputs
Altmetric has tracked 23,979,951 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 372 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one has done particularly well, scoring higher than 98% 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 444,439 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 94% of its contemporaries.
We're also able to compare this research output to 7 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