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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SMASH – semi-automatic muscle analysis using segmentation of histology: a MATLAB application
|
|---|---|
| Published in |
Skeletal Muscle, November 2014
|
| DOI | 10.1186/2044-5040-4-21 |
| Pubmed ID | |
| Authors |
Lucas R Smith, Elisabeth R Barton |
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 % |
|---|---|---|
| United States | 4 | 67% |
| United Kingdom | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 166 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | <1% |
| France | 1 | <1% |
| Brazil | 1 | <1% |
| United Kingdom | 1 | <1% |
| Belgium | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 160 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 49 | 30% |
| Researcher | 33 | 20% |
| Student > Master | 17 | 10% |
| Student > Bachelor | 12 | 7% |
| Student > Doctoral Student | 8 | 5% |
| Other | 22 | 13% |
| Unknown | 25 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 41 | 25% |
| Agricultural and Biological Sciences | 23 | 14% |
| Engineering | 20 | 12% |
| Medicine and Dentistry | 19 | 11% |
| Neuroscience | 11 | 7% |
| Other | 22 | 13% |
| Unknown | 30 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 05 March 2024.
All research outputs
#5,201,825
of 25,508,813 outputs
Outputs from Skeletal Muscle
#129
of 390 outputs
Outputs of similar age
#68,531
of 369,985 outputs
Outputs of similar age from Skeletal Muscle
#2
of 7 outputs
Altmetric has tracked 25,508,813 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 390 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has gotten more attention than average, scoring higher than 66% 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 369,985 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 81% 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 5 of them.