| Title |
DisConICA: a Software Package for Assessing Reproducibility of Brain Networks and their Discriminability across Disorders
|
|---|---|
| Published in |
Neuroinformatics, June 2019
|
| DOI | 10.1007/s12021-019-09422-1 |
| Pubmed ID | |
| Authors |
Mohammed A. Syed, Zhi Yang, D. Rangaprakash, Xiaoping Hu, Michael N. Dretsch, Jeffrey S. Katz, Thomas S. Denney, Gopikrishna Deshpande |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 25% |
| Student > Master | 4 | 10% |
| Student > Ph. D. Student | 3 | 8% |
| Professor > Associate Professor | 2 | 5% |
| Other | 2 | 5% |
| Other | 3 | 8% |
| Unknown | 16 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 13% |
| Nursing and Health Professions | 4 | 10% |
| Neuroscience | 3 | 8% |
| Psychology | 3 | 8% |
| Computer Science | 2 | 5% |
| Other | 5 | 13% |
| Unknown | 18 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 13 June 2019.
All research outputs
#15,867,545
of 23,577,761 outputs
Outputs from Neuroinformatics
#256
of 416 outputs
Outputs of similar age
#219,080
of 354,982 outputs
Outputs of similar age from Neuroinformatics
#5
of 6 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 416 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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 354,982 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one.