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Timeline
X Demographics
Mendeley readers
Attention Score in Context
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 |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 11% |
Switzerland | 1 | 11% |
Unknown | 7 | 78% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 8 | 89% |
Scientists | 1 | 11% |
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
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.