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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation
|
|---|---|
| Published in |
Journal of Cheminformatics, October 2022
|
| DOI | 10.1186/s13321-022-00646-z |
| Pubmed ID | |
| Authors |
Morgan Thomas, Noel M. O’Boyle, Andreas Bender, Chris de Graaf |
X Demographics
The data shown below were collected from the profiles of 17 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 Kingdom | 8 | 47% |
| Norway | 1 | 6% |
| United States | 1 | 6% |
| Switzerland | 1 | 6% |
| Sweden | 1 | 6% |
| Unknown | 5 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 53% |
| Members of the public | 7 | 41% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 47 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 15% |
| Student > Ph. D. Student | 4 | 9% |
| Other | 3 | 6% |
| Student > Bachelor | 2 | 4% |
| Lecturer | 1 | 2% |
| Other | 4 | 9% |
| Unknown | 26 | 55% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 4 | 9% |
| Computer Science | 3 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 4% |
| Social Sciences | 2 | 4% |
| Arts and Humanities | 2 | 4% |
| Other | 7 | 15% |
| Unknown | 27 | 57% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 19 June 2023.
All research outputs
#2,983,137
of 23,885,338 outputs
Outputs from Journal of Cheminformatics
#290
of 881 outputs
Outputs of similar age
#61,874
of 426,767 outputs
Outputs of similar age from Journal of Cheminformatics
#4
of 25 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 881 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has gotten more attention than average, scoring higher than 67% 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 426,767 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 85% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.