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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Probabilistic Circuits for Autonomous Learning: A Simulation Study
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, February 2020
|
| DOI | 10.3389/fncom.2020.00014 |
| Pubmed ID | |
| Authors |
Jan Kaiser, Rafatul Faria, Kerem Y. Camsari, Supriyo Datta |
X Demographics
The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 6% |
| United States | 1 | 6% |
| Switzerland | 1 | 6% |
| Serbia | 1 | 6% |
| United Kingdom | 1 | 6% |
| Japan | 1 | 6% |
| Unknown | 10 | 63% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 69% |
| Scientists | 4 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
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 % |
|---|---|---|
| Student > Ph. D. Student | 6 | 32% |
| Student > Master | 2 | 11% |
| Professor | 1 | 5% |
| Student > Bachelor | 1 | 5% |
| Researcher | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 7 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 5 | 26% |
| Computer Science | 2 | 11% |
| Physics and Astronomy | 2 | 11% |
| Social Sciences | 2 | 11% |
| Chemistry | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 6 | 32% |
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 06 June 2020.
All research outputs
#4,186,557
of 25,387,668 outputs
Outputs from Frontiers in Computational Neuroscience
#189
of 1,464 outputs
Outputs of similar age
#85,589
of 383,195 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#6
of 36 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,464 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 87% 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 383,195 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 77% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.