You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep-Learning-Based Multivariate Pattern Analysis (dMVPA): A Tutorial and a Toolbox
|
|---|---|
| Published in |
Frontiers in Human Neuroscience, March 2021
|
| DOI | 10.3389/fnhum.2021.638052 |
| Pubmed ID | |
| Authors |
Karl M. Kuntzelman, Jacob M. Williams, Phui Cheng Lim, Ashok Samal, Prahalada K. Rao, Matthew R. Johnson |
X Demographics
The data shown below were collected from the profiles of 11 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 | 2 | 18% |
| Sri Lanka | 1 | 9% |
| Mexico | 1 | 9% |
| Switzerland | 1 | 9% |
| Canada | 1 | 9% |
| Unknown | 5 | 45% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 82% |
| Scientists | 2 | 18% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 53 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 19% |
| Researcher | 8 | 15% |
| Student > Master | 5 | 9% |
| Student > Bachelor | 4 | 8% |
| Professor > Associate Professor | 3 | 6% |
| Other | 4 | 8% |
| Unknown | 19 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 10 | 19% |
| Psychology | 8 | 15% |
| Agricultural and Biological Sciences | 4 | 8% |
| Computer Science | 4 | 8% |
| Engineering | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 21 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 20 March 2021.
All research outputs
#6,380,021
of 25,393,071 outputs
Outputs from Frontiers in Human Neuroscience
#2,408
of 7,688 outputs
Outputs of similar age
#137,008
of 451,138 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#49
of 180 outputs
Altmetric has tracked 25,393,071 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 7,688 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has gotten more attention than average, scoring higher than 68% 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 451,138 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 69% of its contemporaries.
We're also able to compare this research output to 180 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 72% of its contemporaries.