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Uncertainty-aware prediction of chemical reaction yields with graph neural networks

Overview of attention for article published in Journal of Cheminformatics, January 2022
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

twitter
9 tweeters

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
29 Mendeley
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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
Authors

Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Seokho Kang

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

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 %
Student > Ph. D. Student 5 17%
Unspecified 4 14%
Student > Doctoral Student 3 10%
Researcher 2 7%
Professor > Associate Professor 2 7%
Other 2 7%
Unknown 11 38%
Readers by discipline Count As %
Chemistry 7 24%
Unspecified 4 14%
Chemical Engineering 1 3%
Computer Science 1 3%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 2 7%
Unknown 13 45%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 20 January 2022.
All research outputs
#6,012,673
of 22,950,943 outputs
Outputs from Journal of Cheminformatics
#493
of 840 outputs
Outputs of similar age
#131,800
of 503,645 outputs
Outputs of similar age from Journal of Cheminformatics
#8
of 15 outputs
Altmetric has tracked 22,950,943 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 840 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
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 503,645 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% 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 53% of its contemporaries.