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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using Minimal-Redundant and Maximal-Relevant Whole-Brain Functional Connectivity to Classify Bipolar Disorder
|
|---|---|
| Published in |
Frontiers in Neuroscience, October 2020
|
| DOI | 10.3389/fnins.2020.563368 |
| Pubmed ID | |
| Authors |
Yen-Ling Chen, Pei-Chi Tu, Tzu-Hsuan Huang, Ya-Mei Bai, Tung-Ping Su, Mu-Hong Chen, Yu-Te Wu |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 3 | 13% |
| Researcher | 2 | 8% |
| Student > Master | 2 | 8% |
| Other | 1 | 4% |
| Student > Bachelor | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 15 | 63% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
| Business, Management and Accounting | 1 | 4% |
| Nursing and Health Professions | 1 | 4% |
| Computer Science | 1 | 4% |
| Economics, Econometrics and Finance | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 17 | 71% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 03 November 2020.
All research outputs
#3,256,170
of 25,387,668 outputs
Outputs from Frontiers in Neuroscience
#2,405
of 11,543 outputs
Outputs of similar age
#81,601
of 439,040 outputs
Outputs of similar age from Frontiers in Neuroscience
#178
of 349 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 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,543 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has done well, scoring higher than 78% 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 439,040 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 81% of its contemporaries.
We're also able to compare this research output to 349 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.