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X Demographics
Mendeley readers
Attention Score in Context
| Title |
EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generation
|
|---|---|
| Published in |
Journal of Cheminformatics, September 2020
|
| DOI | 10.1186/s13321-020-00458-z |
| Pubmed ID | |
| Authors |
Jules Leguy, Thomas Cauchy, Marta Glavatskikh, Béatrice Duval, Benoit Da Mota |
X Demographics
The data shown below were collected from the profiles of 23 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 | 4 | 17% |
| Norway | 1 | 4% |
| Chile | 1 | 4% |
| Brazil | 1 | 4% |
| Canada | 1 | 4% |
| Spain | 1 | 4% |
| France | 1 | 4% |
| Unknown | 13 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 12 | 52% |
| Members of the public | 10 | 43% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 79 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 22% |
| Student > Ph. D. Student | 11 | 14% |
| Student > Bachelor | 7 | 9% |
| Other | 7 | 9% |
| Student > Master | 5 | 6% |
| Other | 5 | 6% |
| Unknown | 27 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 22 | 28% |
| Chemical Engineering | 4 | 5% |
| Engineering | 4 | 5% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Computer Science | 4 | 5% |
| Other | 11 | 14% |
| Unknown | 30 | 38% |
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 01 March 2023.
All research outputs
#2,118,739
of 25,713,737 outputs
Outputs from Journal of Cheminformatics
#166
of 981 outputs
Outputs of similar age
#54,569
of 416,539 outputs
Outputs of similar age from Journal of Cheminformatics
#8
of 19 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 416,539 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 86% of its contemporaries.
We're also able to compare this research output to 19 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 57% of its contemporaries.