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A new fast method for inferring multiple consensus trees using k-medoids

Overview of attention for article published in BMC Ecology and Evolution, April 2018
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  • Average Attention Score compared to outputs of the same age

Mentioned by

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5 X users

Citations

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21 Dimensions

Readers on

mendeley
24 Mendeley
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Title
A new fast method for inferring multiple consensus trees using k-medoids
Published in
BMC Ecology and Evolution, April 2018
DOI 10.1186/s12862-018-1163-8
Pubmed ID
Authors

Nadia Tahiri, Matthieu Willems, Vladimir Makarenkov

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 25%
Student > Master 5 21%
Student > Ph. D. Student 4 17%
Professor > Associate Professor 2 8%
Student > Bachelor 1 4%
Other 2 8%
Unknown 4 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 38%
Computer Science 5 21%
Earth and Planetary Sciences 2 8%
Psychology 1 4%
Immunology and Microbiology 1 4%
Other 0 0%
Unknown 6 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 09 October 2018.
All research outputs
#14,988,646
of 26,017,215 outputs
Outputs from BMC Ecology and Evolution
#2,518
of 3,772 outputs
Outputs of similar age
#170,975
of 347,065 outputs
Outputs of similar age from BMC Ecology and Evolution
#39
of 53 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,772 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.6. This one is in the 32nd percentile – i.e., 32% 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 347,065 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.