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Inverse prediction of PuO2 processing conditions using Bayesian seemingly unrelated regression with functional data

Overview of attention for article published in Frontiers in Nuclear Engineering, May 2024
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Title
Inverse prediction of PuO2 processing conditions using Bayesian seemingly unrelated regression with functional data
Published in
Frontiers in Nuclear Engineering, May 2024
DOI 10.3389/fnuen.2024.1331349
Authors

Audrey Lamson McCombs, Madeline Anne Stricklin, Katherine Goode, J. Gabriel Huerta, Kurtis Shuler, J. Derek Tucker, Adah Zhang, Lucas Sweet, Daniel Ries

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Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 02 June 2024.
All research outputs
#21,214,790
of 26,052,823 outputs
Outputs from Frontiers in Nuclear Engineering
#9
of 17 outputs
Outputs of similar age
#103,520
of 155,725 outputs
Outputs of similar age from Frontiers in Nuclear Engineering
#2
of 3 outputs
Altmetric has tracked 26,052,823 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 17 research outputs from this source. They receive a mean Attention Score of 4.6. This one scored the same or higher as 8 of them.
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We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.