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Probabilistic model building in genetic programming: a critical review

Overview of attention for article published in Genetic Programming and Evolvable Machines, September 2013
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1 X user

Citations

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Readers on

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41 Mendeley
Title
Probabilistic model building in genetic programming: a critical review
Published in
Genetic Programming and Evolvable Machines, September 2013
DOI 10.1007/s10710-013-9205-x
Authors

Kangil Kim, Yin Shan, Xuan Hoai Nguyen, R. I. McKay

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

Geographical breakdown

Country Count As %
Japan 1 2%
Spain 1 2%
Unknown 39 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 27%
Student > Master 4 10%
Student > Bachelor 4 10%
Student > Doctoral Student 3 7%
Professor 3 7%
Other 7 17%
Unknown 9 22%
Readers by discipline Count As %
Computer Science 20 49%
Engineering 8 20%
Economics, Econometrics and Finance 2 5%
Biochemistry, Genetics and Molecular Biology 1 2%
Unknown 10 24%
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 06 June 2014.
All research outputs
#18,373,576
of 22,757,090 outputs
Outputs from Genetic Programming and Evolvable Machines
#110
of 121 outputs
Outputs of similar age
#150,198
of 201,981 outputs
Outputs of similar age from Genetic Programming and Evolvable Machines
#2
of 3 outputs
Altmetric has tracked 22,757,090 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 121 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 5th percentile – i.e., 5% 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 201,981 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
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.