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Domain-Informed Neural Networks for Interaction Localization Within Astroparticle Experiments

Overview of attention for article published in arXiv, June 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

twitter
8 X users

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
5 Mendeley
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Title
Domain-Informed Neural Networks for Interaction Localization Within Astroparticle Experiments
Published in
arXiv, June 2022
DOI 10.3389/frai.2022.832909
Pubmed ID
Authors

Shixiao Liang, Aaron Higuera, Christina Peters, Venkat Roy, Waheed U. Bajwa, Hagit Shatkay, Christopher D. Tunnell

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 40%
Student > Ph. D. Student 1 20%
Unspecified 1 20%
Unknown 1 20%
Readers by discipline Count As %
Unspecified 1 20%
Psychology 1 20%
Physics and Astronomy 1 20%
Medicine and Dentistry 1 20%
Unknown 1 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 09 June 2022.
All research outputs
#14,095,539
of 24,093,053 outputs
Outputs from arXiv
#219,358
of 1,020,419 outputs
Outputs of similar age
#184,001
of 431,858 outputs
Outputs of similar age from arXiv
#7,276
of 36,661 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,020,419 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 76% 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 431,858 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 56% of its contemporaries.
We're also able to compare this research output to 36,661 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.