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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A multimodal approach for determining brain networks by jointly modeling functional and structural connectivity
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, February 2015
|
| DOI | 10.3389/fncom.2015.00022 |
| Pubmed ID | |
| Authors |
Wenqiong Xue, F. DuBois Bowman, Anthony V. Pileggi, Andrew R. Mayer |
X Demographics
The data shown below were collected from the profiles of 10 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 Kingdom | 3 | 30% |
| United States | 2 | 20% |
| Germany | 1 | 10% |
| Belgium | 1 | 10% |
| Mexico | 1 | 10% |
| Japan | 1 | 10% |
| Unknown | 1 | 10% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 70% |
| Scientists | 3 | 30% |
Mendeley readers
The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| Hong Kong | 1 | 1% |
| Greece | 1 | 1% |
| Unknown | 86 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 27% |
| Researcher | 15 | 17% |
| Student > Master | 13 | 15% |
| Professor | 7 | 8% |
| Student > Doctoral Student | 4 | 4% |
| Other | 14 | 16% |
| Unknown | 12 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 12 | 13% |
| Neuroscience | 12 | 13% |
| Psychology | 12 | 13% |
| Agricultural and Biological Sciences | 9 | 10% |
| Physics and Astronomy | 5 | 6% |
| Other | 18 | 20% |
| Unknown | 21 | 24% |
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 08 March 2016.
All research outputs
#6,360,834
of 25,595,500 outputs
Outputs from Frontiers in Computational Neuroscience
#259
of 1,472 outputs
Outputs of similar age
#65,572
of 269,460 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#9
of 31 outputs
Altmetric has tracked 25,595,500 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,472 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 82% 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 269,460 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 75% of its contemporaries.
We're also able to compare this research output to 31 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 70% of its contemporaries.