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Efficient data acquisition and training of collisional-radiative model artificial neural network surrogates through adaptive parameter space sampling

Overview of attention for article published in Machine Learning: Science and Technology, October 2022
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Mentioned by

twitter
3 X users

Readers on

mendeley
10 Mendeley
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Article details
Title
Efficient data acquisition and training of collisional-radiative model artificial neural network surrogates through adaptive parameter space sampling
Published in
Machine Learning: Science and Technology, October 2022
DOI 10.1088/2632-2153/ac93e7
Authors

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Timeline Attention over time Attention Score history
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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 3 30%
Student > Ph. D. Student 2 20%
Student > Doctoral Student 1 10%
Unknown 4 40%
Readers by discipline
Readers by discipline Count As %
Computer Science 2 20%
Physics and Astronomy 2 20%
Mathematics 1 10%
Unknown 5 50%
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 April 2023.
All research outputs
#17,590,020
of 27,446,008 outputs
Outputs from Machine Learning: Science and Technology
#585
of 762 outputs
Outputs of similar age
#226,461
of 448,551 outputs
Outputs of similar age from Machine Learning: Science and Technology
#25
of 28 outputs
Altmetric has tracked 27,446,008 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 762 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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 448,551 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.