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Early warning research on enterprise carbon emission reduction credit risk based on deep learning model under unbalanced data

Overview of attention for article published in Frontiers in Energy Research, November 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
5 Mendeley
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Title
Early warning research on enterprise carbon emission reduction credit risk based on deep learning model under unbalanced data
Published in
Frontiers in Energy Research, November 2023
DOI 10.3389/fenrg.2023.1274425
Authors

Zhi Long, Xiangzhou Chen

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.
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 %
Student > Master 2 40%
Professor > Associate Professor 1 20%
Unknown 2 40%
Readers by discipline Count As %
Engineering 2 40%
Computer Science 1 20%
Unknown 2 40%
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 28 November 2023.
All research outputs
#20,398,621
of 25,071,270 outputs
Outputs from Frontiers in Energy Research
#871
of 4,340 outputs
Outputs of similar age
#184,141
of 268,548 outputs
Outputs of similar age from Frontiers in Energy Research
#19
of 209 outputs
Altmetric has tracked 25,071,270 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,340 research outputs from this source. They receive a mean Attention Score of 1.6. This one has gotten more attention than average, scoring higher than 64% 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 268,548 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 209 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.