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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Uncertainty-aware prediction of chemical reaction yields with graph neural networks
|
|---|---|
| Published in |
Journal of Cheminformatics, January 2022
|
| DOI | 10.1186/s13321-021-00579-z |
| Pubmed ID | |
| Authors |
Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Seokho Kang |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 22% |
| France | 1 | 11% |
| Netherlands | 1 | 11% |
| Unknown | 5 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 67% |
| Scientists | 2 | 22% |
| Science communicators (journalists, bloggers, editors) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 45 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 13% |
| Researcher | 6 | 13% |
| Student > Doctoral Student | 4 | 9% |
| Student > Master | 3 | 7% |
| Professor > Associate Professor | 2 | 4% |
| Other | 2 | 4% |
| Unknown | 22 | 49% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 12 | 27% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 4% |
| Biochemistry, Genetics and Molecular Biology | 2 | 4% |
| Computer Science | 2 | 4% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 24 | 53% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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
#4,495,607
of 25,035,235 outputs
Outputs from Journal of Cheminformatics
#407
of 940 outputs
Outputs of similar age
#103,401
of 517,028 outputs
Outputs of similar age from Journal of Cheminformatics
#5
of 15 outputs
Altmetric has tracked 25,035,235 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 940 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has gotten more attention than average, scoring higher than 56% 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 517,028 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 79% of its contemporaries.
We're also able to compare this research output to 15 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 73% of its contemporaries.