The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, May 2022
|
| DOI | 10.3389/fninf.2022.884180 |
| Pubmed ID | |
| Authors |
Benedikt Feldotto, Jochen Martin Eppler, Cristian Jimenez-Romero, Christopher Bignamini, Carlos Enrique Gutierrez, Ugo Albanese, Eloy Retamino, Viktor Vorobev, Vahid Zolfaghari, Alex Upton, Zhe Sun, Hiroshi Yamaura, Morteza Heidarinejad, Wouter Klijn, Abigail Morrison, Felipe Cruz, Colin McMurtrie, Alois C. Knoll, Jun Igarashi, Tadashi Yamazaki, Kenji Doya, Fabrice O. Morin |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Poland | 1 | 8% |
| Unknown | 11 | 92% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 92% |
| Scientists | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 14% |
| Student > Ph. D. Student | 3 | 14% |
| Unspecified | 2 | 10% |
| Student > Bachelor | 2 | 10% |
| Student > Master | 2 | 10% |
| Other | 2 | 10% |
| Unknown | 7 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 14% |
| Engineering | 3 | 14% |
| Unspecified | 2 | 10% |
| Business, Management and Accounting | 2 | 10% |
| Neuroscience | 2 | 10% |
| Other | 1 | 5% |
| Unknown | 8 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 04 July 2022.
All research outputs
#3,811,845
of 24,053,881 outputs
Outputs from Frontiers in Neuroinformatics
#205
of 789 outputs
Outputs of similar age
#78,356
of 429,378 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#2
of 34 outputs
Altmetric has tracked 24,053,881 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 789 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has gotten more attention than average, scoring higher than 73% 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 429,378 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 34 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 94% of its contemporaries.