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An explainable integrated machine learning model for mapping soil erosion by wind and water in a catchment with three desiccated lakes

Overview of attention for article published in Aeolian Research, September 2024
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Mentioned by

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3 X users

Citations

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1 Dimensions

Readers on

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9 Mendeley
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Title
An explainable integrated machine learning model for mapping soil erosion by wind and water in a catchment with three desiccated lakes
Published in
Aeolian Research, September 2024
DOI 10.1016/j.aeolia.2024.100924
Authors

Hamid Gholami, Mehdi Jalali, Marzieh Rezaei, Aliakbar Mohamadifar, Yougui Song, Yue Li, Yanping Wang, Baicheng Niu, Ebrahim Omidvar, Dimitris G. Kaskaoutis

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 11%
Student > Ph. D. Student 1 11%
Researcher 1 11%
Lecturer 1 11%
Unknown 5 56%
Readers by discipline Count As %
Unspecified 1 11%
Earth and Planetary Sciences 1 11%
Social Sciences 1 11%
Unknown 6 67%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 30 April 2024.
All research outputs
#16,367,671
of 25,838,141 outputs
Outputs from Aeolian Research
#119
of 247 outputs
Outputs of similar age
#867
of 1,474 outputs
Outputs of similar age from Aeolian Research
#1
of 3 outputs
Altmetric has tracked 25,838,141 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 247 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 48th percentile – i.e., 48% 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 1,474 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% 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. This one has scored higher than all of them