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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mol-CycleGAN: a generative model for molecular optimization
|
|---|---|
| Published in |
Journal of Cheminformatics, January 2020
|
| DOI | 10.1186/s13321-019-0404-1 |
| Pubmed ID | |
| Authors |
Łukasz Maziarka, Agnieszka Pocha, Jan Kaczmarczyk, Krzysztof Rataj, Tomasz Danel, Michał Warchoł |
X Demographics
The data shown below were collected from the profiles of 19 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 | 16% |
| Japan | 2 | 11% |
| United Kingdom | 1 | 5% |
| Unknown | 13 | 68% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 13 | 68% |
| Scientists | 5 | 26% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 252 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 252 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 43 | 17% |
| Researcher | 40 | 16% |
| Student > Master | 35 | 14% |
| Student > Bachelor | 18 | 7% |
| Student > Doctoral Student | 9 | 4% |
| Other | 28 | 11% |
| Unknown | 79 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 49 | 19% |
| Chemistry | 41 | 16% |
| Biochemistry, Genetics and Molecular Biology | 22 | 9% |
| Engineering | 11 | 4% |
| Chemical Engineering | 9 | 4% |
| Other | 34 | 13% |
| Unknown | 86 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 33. 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 September 2022.
All research outputs
#1,216,292
of 25,385,509 outputs
Outputs from Journal of Cheminformatics
#50
of 961 outputs
Outputs of similar age
#29,649
of 473,044 outputs
Outputs of similar age from Journal of Cheminformatics
#2
of 22 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 961 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one has done particularly well, scoring higher than 94% 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 473,044 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 93% of its contemporaries.
We're also able to compare this research output to 22 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 90% of its contemporaries.