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Explainable Machine Learning Approach Quantified the Long-Term (1981–2015) Impact of Climate and Soil Properties on Yields of Major Agricultural Crops Across CONUS

Overview of attention for article published in Frontiers in Sustainable Food Systems, April 2022
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#44 of 2,467)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
12 news outlets
blogs
3 blogs
twitter
12 X users

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
43 Mendeley
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Title
Explainable Machine Learning Approach Quantified the Long-Term (1981–2015) Impact of Climate and Soil Properties on Yields of Major Agricultural Crops Across CONUS
Published in
Frontiers in Sustainable Food Systems, April 2022
DOI 10.3389/fsufs.2022.847892
Authors

Debjani Sihi, Biswanath Dari, Abraham Peedikayil Kuruvila, Gaurav Jha, Kanad Basu

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 16%
Student > Master 5 12%
Student > Ph. D. Student 5 12%
Lecturer 3 7%
Student > Bachelor 3 7%
Other 7 16%
Unknown 13 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 30%
Environmental Science 3 7%
Computer Science 3 7%
Biochemistry, Genetics and Molecular Biology 2 5%
Business, Management and Accounting 2 5%
Other 7 16%
Unknown 13 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 108. 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 31 August 2022.
All research outputs
#376,606
of 24,849,927 outputs
Outputs from Frontiers in Sustainable Food Systems
#44
of 2,467 outputs
Outputs of similar age
#10,256
of 435,037 outputs
Outputs of similar age from Frontiers in Sustainable Food Systems
#2
of 160 outputs
Altmetric has tracked 24,849,927 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,467 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one has done particularly well, scoring higher than 98% 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 435,037 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 97% of its contemporaries.
We're also able to compare this research output to 160 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 99% of its contemporaries.