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X Demographics
Mendeley readers
Attention Score in Context
| Title |
One Rule to Grow Them All: A General Theory of Neuronal Branching and Its Practical Application
|
|---|---|
| Published in |
PLoS Computational Biology, August 2010
|
| DOI | 10.1371/journal.pcbi.1000877 |
| Pubmed ID | |
| Authors |
Hermann Cuntz, Friedrich Forstner, Alexander Borst, Michael Häusser |
X Demographics
The data shown below were collected from the profiles of 19 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 | 16% |
| Ireland | 2 | 11% |
| Germany | 2 | 11% |
| Canada | 2 | 11% |
| Austria | 1 | 5% |
| United Kingdom | 1 | 5% |
| Unknown | 8 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 17 | 89% |
| Scientists | 2 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 547 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 16 | 3% |
| United Kingdom | 13 | 2% |
| United States | 10 | 2% |
| Portugal | 3 | <1% |
| Spain | 3 | <1% |
| Japan | 2 | <1% |
| Canada | 2 | <1% |
| Israel | 1 | <1% |
| Norway | 1 | <1% |
| Other | 11 | 2% |
| Unknown | 485 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 154 | 28% |
| Researcher | 127 | 23% |
| Student > Master | 71 | 13% |
| Student > Bachelor | 44 | 8% |
| Professor > Associate Professor | 22 | 4% |
| Other | 77 | 14% |
| Unknown | 52 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 176 | 32% |
| Neuroscience | 116 | 21% |
| Computer Science | 50 | 9% |
| Physics and Astronomy | 35 | 6% |
| Engineering | 31 | 6% |
| Other | 76 | 14% |
| Unknown | 63 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 46. 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 30 November 2023.
All research outputs
#900,009
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#674
of 8,964 outputs
Outputs of similar age
#2,474
of 104,172 outputs
Outputs of similar age from PLoS Computational Biology
#1
of 62 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done particularly well, scoring higher than 92% 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 104,172 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 97% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.