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Machine Learning Prediction of the Three Main Input Parameters of a Simplified Physiologically Based Pharmacokinetic Model Subsequently Used to Generate Time-Dependent Plasma Concentration Data in…

Overview of attention for article published in Biological and Pharmaceutical Bulletin, November 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

news
1 news outlet
twitter
1 X user

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
12 Mendeley
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Title
Machine Learning Prediction of the Three Main Input Parameters of a Simplified Physiologically Based Pharmacokinetic Model Subsequently Used to Generate Time-Dependent Plasma Concentration Data in Humans after Oral Doses of 212 Disparate Chemicals
Published in
Biological and Pharmaceutical Bulletin, November 2021
DOI 10.1248/bpb.b21-00769
Pubmed ID
Authors

Yusuke Kamiya, Kentaro Handa, Tomonori Miura, Junya Ohori, Airi Kato, Makiko Shimizu, Masato Kitajima, Hiroshi Yamazaki

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 17%
Researcher 2 17%
Unspecified 1 8%
Lecturer 1 8%
Unknown 6 50%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 2 17%
Unspecified 1 8%
Social Sciences 1 8%
Medicine and Dentistry 1 8%
Unknown 7 58%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 18 January 2022.
All research outputs
#5,245,461
of 25,392,582 outputs
Outputs from Biological and Pharmaceutical Bulletin
#368
of 3,268 outputs
Outputs of similar age
#110,649
of 443,745 outputs
Outputs of similar age from Biological and Pharmaceutical Bulletin
#3
of 36 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,268 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done well, scoring higher than 88% 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 443,745 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 74% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.