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Snow avalanche susceptibility mapping using novel tree-based machine learning algorithms (XGBoost, NGBoost, and LightGBM) with eXplainable Artificial Intelligence (XAI) approach

Overview of attention for article published in Stochastic Environmental Research and Risk Assessment, March 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
34 Mendeley
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Title
Snow avalanche susceptibility mapping using novel tree-based machine learning algorithms (XGBoost, NGBoost, and LightGBM) with eXplainable Artificial Intelligence (XAI) approach
Published in
Stochastic Environmental Research and Risk Assessment, March 2023
DOI 10.1007/s00477-023-02392-6
Authors

Muzaffer Can IBAN, Suleyman Sefa BILGILIOGLU

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 6 18%
Researcher 5 15%
Student > Ph. D. Student 3 9%
Professor > Associate Professor 2 6%
Lecturer 1 3%
Other 3 9%
Unknown 14 41%
Readers by discipline Count As %
Unspecified 6 18%
Engineering 4 12%
Computer Science 4 12%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Business, Management and Accounting 1 3%
Other 2 6%
Unknown 16 47%
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 13 March 2023.
All research outputs
#14,075,458
of 23,839,820 outputs
Outputs from Stochastic Environmental Research and Risk Assessment
#112
of 239 outputs
Outputs of similar age
#173,861
of 420,803 outputs
Outputs of similar age from Stochastic Environmental Research and Risk Assessment
#2
of 4 outputs
Altmetric has tracked 23,839,820 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 239 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has gotten more attention than average, scoring higher than 51% 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 420,803 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.