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Hilbert series, machine learning, and applications to physics

Overview of attention for article published in Physics Letters B, April 2022
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
8 Mendeley
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Title
Hilbert series, machine learning, and applications to physics
Published in
Physics Letters B, April 2022
DOI 10.1016/j.physletb.2022.136966
Authors

Jiakang Bao, Yang-Hui He, Edward Hirst, Johannes Hofscheier, Alexander Kasprzyk, Suvajit Majumder

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Researcher 2 25%
Student > Bachelor 1 13%
Unknown 3 38%
Readers by discipline Count As %
Physics and Astronomy 3 38%
Computer Science 1 13%
Engineering 1 13%
Unknown 3 38%
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 08 March 2022.
All research outputs
#16,734,944
of 25,387,668 outputs
Outputs from Physics Letters B
#4,135
of 10,416 outputs
Outputs of similar age
#252,164
of 447,715 outputs
Outputs of similar age from Physics Letters B
#41
of 109 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,416 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 55% 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 447,715 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 109 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 61% of its contemporaries.