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Utilization of risk-based predictive stability within regulatory submissions; industry’s experience

Overview of attention for article published in AAPS Open, May 2020
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
21 Mendeley
Title
Utilization of risk-based predictive stability within regulatory submissions; industry’s experience
Published in
AAPS Open, May 2020
DOI 10.1186/s41120-020-00034-7
Authors

Megan McMahon, Helen Williams, Elke Debie, Mingkun Fu, Robert Bujalski, Fenghe Qiu, Yan Wu, Hanlin Li, Jin Wang, Cherokee Hoaglund-Hyzer, Donnie Pulliam

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 %
Researcher 4 19%
Student > Master 4 19%
Other 3 14%
Student > Doctoral Student 1 5%
Student > Ph. D. Student 1 5%
Other 2 10%
Unknown 6 29%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 7 33%
Chemistry 2 10%
Environmental Science 1 5%
Chemical Engineering 1 5%
Business, Management and Accounting 1 5%
Other 3 14%
Unknown 6 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 12 November 2020.
All research outputs
#6,026,259
of 23,262,131 outputs
Outputs from AAPS Open
#8
of 33 outputs
Outputs of similar age
#124,993
of 385,688 outputs
Outputs of similar age from AAPS Open
#1
of 1 outputs
Altmetric has tracked 23,262,131 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 33 research outputs from this source. They receive a mean Attention Score of 3.4. This one scored the same or higher as 25 of them.
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 385,688 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 67% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them