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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Learning, Memory, and the Role of Neural Network Architecture
|
|---|---|
| Published in |
PLoS Computational Biology, June 2011
|
| DOI | 10.1371/journal.pcbi.1002063 |
| Pubmed ID | |
| Authors |
Ann M. Hermundstad, Kevin S. Brown, Danielle S. Bassett, Jean M. Carlson |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 2 | 20% |
| Germany | 1 | 10% |
| United Kingdom | 1 | 10% |
| France | 1 | 10% |
| Switzerland | 1 | 10% |
| Colombia | 1 | 10% |
| Portugal | 1 | 10% |
| Unknown | 2 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 50% |
| Members of the public | 4 | 40% |
| Science communicators (journalists, bloggers, editors) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 169 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 3% |
| Germany | 2 | 1% |
| France | 1 | <1% |
| Sweden | 1 | <1% |
| Netherlands | 1 | <1% |
| Belarus | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Belgium | 1 | <1% |
| United Kingdom | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 151 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 46 | 27% |
| Researcher | 33 | 20% |
| Student > Master | 24 | 14% |
| Student > Bachelor | 17 | 10% |
| Professor | 11 | 7% |
| Other | 20 | 12% |
| Unknown | 18 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 19% |
| Computer Science | 27 | 16% |
| Neuroscience | 25 | 15% |
| Psychology | 16 | 9% |
| Physics and Astronomy | 14 | 8% |
| Other | 33 | 20% |
| Unknown | 22 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 08 February 2021.
All research outputs
#2,485,722
of 25,374,917 outputs
Outputs from PLoS Computational Biology
#2,248
of 8,960 outputs
Outputs of similar age
#11,639
of 126,660 outputs
Outputs of similar age from PLoS Computational Biology
#13
of 65 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,960 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 gotten more attention than average, scoring higher than 74% 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 126,660 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 90% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.