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Explainable deep-learning framework: decoding brain states and prediction of individual performance in false-belief task at early childhood stage

Overview of attention for article published in Frontiers in Neuroinformatics, June 2024
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  • Average Attention Score compared to outputs of the same age

Mentioned by

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2 X users

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mendeley
4 Mendeley
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Title
Explainable deep-learning framework: decoding brain states and prediction of individual performance in false-belief task at early childhood stage
Published in
Frontiers in Neuroinformatics, June 2024
DOI 10.3389/fninf.2024.1392661
Pubmed ID
Authors

Km Bhavna, Azman Akhter, Romi Banerjee, Dipanjan Roy

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

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 25%
Lecturer 1 25%
Unknown 2 50%
Readers by discipline Count As %
Unspecified 1 25%
Business, Management and Accounting 1 25%
Unknown 2 50%
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 June 2024.
All research outputs
#17,897,145
of 26,205,030 outputs
Outputs from Frontiers in Neuroinformatics
#605
of 851 outputs
Outputs of similar age
#72,899
of 149,408 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#2
of 2 outputs
Altmetric has tracked 26,205,030 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 851 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 23rd percentile – i.e., 23% 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 149,408 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.