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Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients

Overview of attention for article published in Journal of Cheminformatics, February 2015
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

twitter
1 X user
patent
1 patent

Citations

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24 Dimensions

Readers on

mendeley
55 Mendeley
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Title
Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients
Published in
Journal of Cheminformatics, February 2015
DOI 10.1186/s13321-015-0054-x
Pubmed ID
Authors

Alex A Freitas, Kriti Limbu, Taravat Ghafourian

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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Brazil 2 4%
Portugal 1 2%
Unknown 50 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 18%
Researcher 10 18%
Student > Master 8 15%
Student > Bachelor 6 11%
Student > Doctoral Student 4 7%
Other 6 11%
Unknown 11 20%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 8 15%
Chemistry 7 13%
Engineering 7 13%
Agricultural and Biological Sciences 4 7%
Computer Science 4 7%
Other 10 18%
Unknown 15 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 14 March 2024.
All research outputs
#8,049,150
of 25,611,630 outputs
Outputs from Journal of Cheminformatics
#616
of 978 outputs
Outputs of similar age
#85,280
of 270,708 outputs
Outputs of similar age from Journal of Cheminformatics
#7
of 21 outputs
Altmetric has tracked 25,611,630 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 978 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 10.0. This one is in the 36th percentile – i.e., 36% 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 270,708 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 21 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.