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An evolutionary variational autoencoder for perovskite discovery

Overview of attention for article published in Frontiers in Materials, September 2023
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

twitter
2 X users

Readers on

mendeley
3 Mendeley
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Title
An evolutionary variational autoencoder for perovskite discovery
Published in
Frontiers in Materials, September 2023
DOI 10.3389/fmats.2023.1233961
Authors

Ericsson Tetteh Chenebuah, Michel Nganbe, Alain Beaudelaire Tchagang

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 67%
Unspecified 1 33%
Readers by discipline Count As %
Unspecified 1 33%
Physics and Astronomy 1 33%
Engineering 1 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 December 2023.
All research outputs
#16,352,500
of 25,058,660 outputs
Outputs from Frontiers in Materials
#310
of 2,983 outputs
Outputs of similar age
#171,117
of 340,270 outputs
Outputs of similar age from Frontiers in Materials
#3
of 114 outputs
Altmetric has tracked 25,058,660 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,983 research outputs from this source. They receive a mean Attention Score of 1.6. This one has done well, scoring higher than 88% 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 340,270 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 114 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 97% of its contemporaries.