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X Demographics
Mendeley readers
Attention Score in Context
| Title |
ErtlFunctionalGroupsFinder: automated rule-based functional group detection with the Chemistry Development Kit (CDK)
|
|---|---|
| Published in |
Journal of Cheminformatics, June 2019
|
| DOI | 10.1186/s13321-019-0361-8 |
| Pubmed ID | |
| Authors |
Sebastian Fritsch, Stefan Neumann, Jonas Schaub, Christoph Steinbeck, Achim Zielesny |
X Demographics
The data shown below were collected from the profiles of 29 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 4 | 14% |
| Sweden | 3 | 10% |
| Germany | 3 | 10% |
| United States | 2 | 7% |
| United Kingdom | 2 | 7% |
| Spain | 1 | 3% |
| Japan | 1 | 3% |
| Switzerland | 1 | 3% |
| Unknown | 12 | 41% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 19 | 66% |
| Members of the public | 9 | 31% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 28% |
| Student > Ph. D. Student | 5 | 17% |
| Student > Master | 3 | 10% |
| Student > Bachelor | 2 | 7% |
| Other | 2 | 7% |
| Other | 4 | 14% |
| Unknown | 5 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 10 | 34% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 14% |
| Agricultural and Biological Sciences | 2 | 7% |
| Biochemistry, Genetics and Molecular Biology | 2 | 7% |
| Medicine and Dentistry | 2 | 7% |
| Other | 4 | 14% |
| Unknown | 5 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 21 September 2019.
All research outputs
#2,092,282
of 25,713,737 outputs
Outputs from Journal of Cheminformatics
#163
of 981 outputs
Outputs of similar age
#44,036
of 367,802 outputs
Outputs of similar age from Journal of Cheminformatics
#6
of 18 outputs
Altmetric has tracked 25,713,737 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 981 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 10.0. This one has done well, scoring higher than 83% 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 367,802 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 88% of its contemporaries.
We're also able to compare this research output to 18 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 66% of its contemporaries.