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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Is predictive coding theory articulated enough to be testable?
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, September 2015
|
| DOI | 10.3389/fncom.2015.00111 |
| Pubmed ID | |
| Authors |
Naoki Kogo, Chris Trengove |
X Demographics
The data shown below were collected from the profiles of 7 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 | 1 | 14% |
| Netherlands | 1 | 14% |
| United Kingdom | 1 | 14% |
| Mexico | 1 | 14% |
| Germany | 1 | 14% |
| Switzerland | 1 | 14% |
| Unknown | 1 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 217 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 2 | <1% |
| Portugal | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 213 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 66 | 30% |
| Researcher | 35 | 16% |
| Student > Master | 35 | 16% |
| Student > Bachelor | 20 | 9% |
| Student > Doctoral Student | 10 | 5% |
| Other | 31 | 14% |
| Unknown | 20 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 64 | 29% |
| Psychology | 55 | 25% |
| Agricultural and Biological Sciences | 17 | 8% |
| Computer Science | 9 | 4% |
| Physics and Astronomy | 9 | 4% |
| Other | 33 | 15% |
| Unknown | 30 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 23 April 2020.
All research outputs
#4,179,510
of 22,826,360 outputs
Outputs from Frontiers in Computational Neuroscience
#190
of 1,343 outputs
Outputs of similar age
#54,055
of 267,498 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#5
of 36 outputs
Altmetric has tracked 22,826,360 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,343 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done well, scoring higher than 85% 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 267,498 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 78% 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 86% of its contemporaries.