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GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments

Overview of attention for article published in arXiv, January 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
9 X users

Readers on

mendeley
21 Mendeley
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Title
GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments
Published in
arXiv, January 2021
DOI 10.3389/fdata.2020.604083
Pubmed ID
Authors

Michael Wang, Tingjun Yang, Maria Acosta Flechas, Philip Harris, Benjamin Hawks, Burt Holzman, Kyle Knoepfel, Jeffrey Krupa, Kevin Pedro, Nhan Tran

Timeline

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X Demographics

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.
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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 24%
Lecturer 1 5%
Student > Master 1 5%
Unknown 14 67%
Readers by discipline Count As %
Computer Science 4 19%
Engineering 2 10%
Earth and Planetary Sciences 1 5%
Unknown 14 67%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 29 March 2021.
All research outputs
#8,268,461
of 25,387,668 outputs
Outputs from arXiv
#146,099
of 915,148 outputs
Outputs of similar age
#196,510
of 523,384 outputs
Outputs of similar age from arXiv
#4,152
of 24,760 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 915,148 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 83% 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 523,384 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 61% of its contemporaries.
We're also able to compare this research output to 24,760 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.