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A machine learning approach to predict perceptual decisions: an insight into face pareidolia

Overview of attention for article published in Brain Informatics, February 2019
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Mentioned by

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1 X user

Citations

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14 Dimensions

Readers on

mendeley
57 Mendeley
Title
A machine learning approach to predict perceptual decisions: an insight into face pareidolia
Published in
Brain Informatics, February 2019
DOI 10.1186/s40708-019-0094-5
Pubmed ID
Authors

Kasturi Barik, Syed Naser Daimi, Rhiannon Jones, Joydeep Bhattacharya, Goutam Saha

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 19%
Student > Ph. D. Student 8 14%
Student > Bachelor 8 14%
Student > Doctoral Student 4 7%
Lecturer > Senior Lecturer 3 5%
Other 10 18%
Unknown 13 23%
Readers by discipline Count As %
Psychology 21 37%
Engineering 6 11%
Neuroscience 5 9%
Computer Science 3 5%
Medicine and Dentistry 2 4%
Other 5 9%
Unknown 15 26%
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 13 February 2019.
All research outputs
#17,119,626
of 25,151,710 outputs
Outputs from Brain Informatics
#78
of 116 outputs
Outputs of similar age
#279,484
of 449,557 outputs
Outputs of similar age from Brain Informatics
#2
of 2 outputs
Altmetric has tracked 25,151,710 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 116 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. 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 449,557 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% 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.