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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning hypothesis-generation for patient stratification and target discovery in rare disease: our experience with Open Science in ALS
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, January 2024
|
| DOI | 10.3389/fncom.2023.1199736 |
| Pubmed ID | |
| Authors |
Joseph Geraci, Ravi Bhargava, Bessi Qorri, Paul Leonchyk, Douglas Cook, Moses Cook, Fanny Sie, Luca Pani |
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 % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 2 | 20% |
| Unspecified | 1 | 10% |
| Professor | 1 | 10% |
| Lecturer | 1 | 10% |
| Unknown | 5 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 2 | 20% |
| Unspecified | 1 | 10% |
| Computer Science | 1 | 10% |
| Medicine and Dentistry | 1 | 10% |
| Unknown | 5 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 47. 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 02 April 2024.
All research outputs
#905,069
of 25,622,179 outputs
Outputs from Frontiers in Computational Neuroscience
#37
of 1,472 outputs
Outputs of similar age
#13,838
of 347,339 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#2
of 26 outputs
Altmetric has tracked 25,622,179 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% 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 particularly well, scoring higher than 97% 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 347,339 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.