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Watershed scale soil moisture estimation model using machine learning and remote sensing in a data-scarce context

Overview of attention for article published in Scientia Agropecuaria, March 2024
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  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 X user

Readers on

mendeley
4 Mendeley
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Title
Watershed scale soil moisture estimation model using machine learning and remote sensing in a data-scarce context
Published in
Scientia Agropecuaria, March 2024
DOI 10.17268/sci.agropecu.2024.008
Authors

Marcelo Bueno Dueñas, Carlos Baca García, Nilton Montoya, Pedro Rau, Hildo Loayza

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

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 50%
Lecturer 2 50%
Readers by discipline Count As %
Unspecified 2 50%
Social Sciences 2 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 May 2024.
All research outputs
#17,683,640
of 25,923,151 outputs
Outputs from Scientia Agropecuaria
#26
of 40 outputs
Outputs of similar age
#177,656
of 336,592 outputs
Outputs of similar age from Scientia Agropecuaria
#3
of 3 outputs
Altmetric has tracked 25,923,151 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 40 research outputs from this source. They receive a mean Attention Score of 4.2. This one scored the same or higher as 14 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 336,592 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.