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Revisiting the Geochemical Classification of Zircon Source Rocks Using a Machine Learning Approach

Overview of attention for article published in Mathematical Geosciences, January 2024
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#27 of 299)
  • Good Attention Score compared to outputs of the same age (76th percentile)

Mentioned by

twitter
10 X users

Readers on

mendeley
11 Mendeley
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Title
Revisiting the Geochemical Classification of Zircon Source Rocks Using a Machine Learning Approach
Published in
Mathematical Geosciences, January 2024
DOI 10.1007/s11004-023-10128-z
Authors

Keita Itano, Hikaru Sawada

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 18%
Student > Doctoral Student 2 18%
Other 1 9%
Lecturer 1 9%
Student > Master 1 9%
Other 1 9%
Unknown 3 27%
Readers by discipline Count As %
Earth and Planetary Sciences 6 55%
Computer Science 1 9%
Engineering 1 9%
Unknown 3 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 18 January 2024.
All research outputs
#5,503,208
of 26,329,145 outputs
Outputs from Mathematical Geosciences
#27
of 299 outputs
Outputs of similar age
#86,552
of 376,405 outputs
Outputs of similar age from Mathematical Geosciences
#1
of 3 outputs
Altmetric has tracked 26,329,145 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 299 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 90% 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 376,405 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
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