↓ Skip to main content

Molecular Factor Computing for Predictive Spectroscopy

Overview of attention for article published in Pharmaceutical Research, March 2007
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

patent
27 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
15 Mendeley
Title
Molecular Factor Computing for Predictive Spectroscopy
Published in
Pharmaceutical Research, March 2007
DOI 10.1007/s11095-007-9260-1
Pubmed ID
Authors

Bin Dai, Aaron Urbas, Craig C. Douglas, Robert A. Lodder

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 %
Japan 1 7%
Finland 1 7%
Unknown 13 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 27%
Student > Master 3 20%
Professor > Associate Professor 3 20%
Professor 2 13%
Researcher 2 13%
Other 1 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 27%
Engineering 4 27%
Chemistry 3 20%
Computer Science 2 13%
Chemical Engineering 1 7%
Other 1 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 11 July 2017.
All research outputs
#2,008,588
of 22,880,230 outputs
Outputs from Pharmaceutical Research
#85
of 2,860 outputs
Outputs of similar age
#4,583
of 76,981 outputs
Outputs of similar age from Pharmaceutical Research
#2
of 57 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,860 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has done particularly well, scoring higher than 96% 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 76,981 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 57 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 96% of its contemporaries.