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Interpretable machine learning model for shear wave estimation in a carbonate reservoir using LightGBM and SHAP: a case study in the Amu Darya right bank

Overview of attention for article published in Frontiers in Earth Science, October 2023
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Mentioned by

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1 X user

Citations

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1 Dimensions

Readers on

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5 Mendeley
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Title
Interpretable machine learning model for shear wave estimation in a carbonate reservoir using LightGBM and SHAP: a case study in the Amu Darya right bank
Published in
Frontiers in Earth Science, October 2023
DOI 10.3389/feart.2023.1217384
Authors

Tianze Zhang, Hui Chai, Hongjun Wang, Tongcui Guo, Liangjie Zhang, Wenqi Zhang

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

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 40%
Student > Bachelor 1 20%
Researcher 1 20%
Unknown 1 20%
Readers by discipline Count As %
Unspecified 2 40%
Economics, Econometrics and Finance 1 20%
Engineering 1 20%
Unknown 1 20%
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 19 October 2023.
All research outputs
#22,081,574
of 24,639,073 outputs
Outputs from Frontiers in Earth Science
#3,569
of 5,813 outputs
Outputs of similar age
#125,107
of 157,376 outputs
Outputs of similar age from Frontiers in Earth Science
#53
of 138 outputs
Altmetric has tracked 24,639,073 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,813 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% 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 157,376 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.