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Bayesian Generalized Linear Model for Simulating Bacterial Inactivation/Growth Considering Variability and Uncertainty

Overview of attention for article published in Frontiers in Microbiology, June 2021
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1 X user

Citations

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9 Dimensions

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15 Mendeley
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Title
Bayesian Generalized Linear Model for Simulating Bacterial Inactivation/Growth Considering Variability and Uncertainty
Published in
Frontiers in Microbiology, June 2021
DOI 10.3389/fmicb.2021.674364
Pubmed ID
Authors

Satoko Hiura, Hiroki Abe, Kento Koyama, Shige Koseki

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 13%
Lecturer 1 7%
Student > Doctoral Student 1 7%
Other 1 7%
Professor 1 7%
Other 1 7%
Unknown 8 53%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 20%
Mathematics 2 13%
Unknown 10 67%
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 30 June 2021.
All research outputs
#22,823,736
of 25,443,857 outputs
Outputs from Frontiers in Microbiology
#27,001
of 29,374 outputs
Outputs of similar age
#390,232
of 455,746 outputs
Outputs of similar age from Frontiers in Microbiology
#1,100
of 1,146 outputs
Altmetric has tracked 25,443,857 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 29,374 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one is in the 1st percentile – i.e., 1% 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 455,746 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,146 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.