The data shown below were collected from the profiles of 9 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 |
Reactive, Proactive, and Inductive Agents: An Evolutionary Path for Biological and Artificial Spiking Networks
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, January 2020
|
| DOI | 10.3389/fncom.2019.00088 |
| Pubmed ID | |
| Authors |
Lana Sinapayen, Atsushi Masumori, Takashi Ikegami |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 11% |
| United States | 1 | 11% |
| Unknown | 7 | 78% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 89% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 37% |
| Student > Bachelor | 2 | 11% |
| Student > Ph. D. Student | 2 | 11% |
| Professor | 1 | 5% |
| Other | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 4 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 21% |
| Agricultural and Biological Sciences | 2 | 11% |
| Engineering | 2 | 11% |
| Physics and Astronomy | 2 | 11% |
| Nursing and Health Professions | 1 | 5% |
| Other | 3 | 16% |
| Unknown | 5 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 19 February 2021.
All research outputs
#7,376,606
of 26,476,278 outputs
Outputs from Frontiers in Computational Neuroscience
#330
of 1,498 outputs
Outputs of similar age
#149,228
of 483,413 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#15
of 35 outputs
Altmetric has tracked 26,476,278 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,498 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done well, scoring higher than 77% 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 483,413 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.