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X Demographics
Mendeley readers
Attention Score in Context
| Title |
R.ROSETTA: an interpretable machine learning framework
|
|---|---|
| Published in |
BMC Bioinformatics, March 2021
|
| DOI | 10.1186/s12859-021-04049-z |
| Pubmed ID | |
| Authors |
Mateusz Garbulowski, Klev Diamanti, Karolina Smolińska, Nicholas Baltzer, Patricia Stoll, Susanne Bornelöv, Aleksander Øhrn, Lars Feuk, Jan Komorowski |
X Demographics
The data shown below were collected from the profiles of 13 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 | 3 | 23% |
| Sweden | 1 | 8% |
| India | 1 | 8% |
| Bolivia, Plurinational State of | 1 | 8% |
| United Kingdom | 1 | 8% |
| Unknown | 6 | 46% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 69% |
| Scientists | 4 | 31% |
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 % |
|---|---|---|
| Researcher | 12 | 23% |
| Student > Bachelor | 4 | 8% |
| Student > Doctoral Student | 4 | 8% |
| Student > Ph. D. Student | 4 | 8% |
| Student > Master | 3 | 6% |
| Other | 6 | 11% |
| Unknown | 20 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 11 | 21% |
| Engineering | 5 | 9% |
| Medicine and Dentistry | 4 | 8% |
| Agricultural and Biological Sciences | 3 | 6% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Other | 2 | 4% |
| Unknown | 25 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 30 April 2021.
All research outputs
#5,190,242
of 24,887,826 outputs
Outputs from BMC Bioinformatics
#1,869
of 7,602 outputs
Outputs of similar age
#120,037
of 427,563 outputs
Outputs of similar age from BMC Bioinformatics
#48
of 152 outputs
Altmetric has tracked 24,887,826 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,602 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 75% 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 427,563 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 71% of its contemporaries.
We're also able to compare this research output to 152 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 69% of its contemporaries.