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Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 2. Applications

Overview of attention for article published in Water Resources Research, July 2010
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Mentioned by

patent
1 patent

Citations

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49 Dimensions

Readers on

mendeley
14 Mendeley
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Title
Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 2. Applications
Published in
Water Resources Research, July 2010
DOI 10.1029/wr019i003p00662
Authors

Richard L. Cooley

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 7%
Unknown 13 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 36%
Student > Ph. D. Student 4 29%
Other 2 14%
Professor 1 7%
Student > Postgraduate 1 7%
Other 0 0%
Unknown 1 7%
Readers by discipline Count As %
Earth and Planetary Sciences 6 43%
Environmental Science 3 21%
Engineering 2 14%
Agricultural and Biological Sciences 1 7%
Unknown 2 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 June 2019.
All research outputs
#8,162,549
of 24,471,305 outputs
Outputs from Water Resources Research
#1,955
of 5,107 outputs
Outputs of similar age
#35,850
of 98,579 outputs
Outputs of similar age from Water Resources Research
#252
of 988 outputs
Altmetric has tracked 24,471,305 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,107 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one is in the 33rd percentile – i.e., 33% 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 98,579 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 988 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.