↓ Skip to main content

The MR-Base platform supports systematic causal inference across the human phenome

Overview of attention for article published in eLife, May 2018
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
57 X users
f1000
1 research highlight platform

Citations

dimensions_citation
3955 Dimensions

Readers on

mendeley
887 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The MR-Base platform supports systematic causal inference across the human phenome
Published in
eLife, May 2018
DOI 10.7554/elife.34408
Pubmed ID
Authors

Gibran Hemani, Jie Zheng, Benjamin Elsworth, Kaitlin H Wade, Valeriia Haberland, Denis Baird, Charles Laurin, Stephen Burgess, Jack Bowden, Ryan Langdon, Vanessa Y Tan, James Yarmolinsky, Hashem A Shihab, Nicholas J Timpson, David M Evans, Caroline Relton, Richard M Martin, George Davey Smith, Tom R Gaunt, Philip C Haycock

X Demographics

X Demographics

The data shown below were collected from the profiles of 57 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 887 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 887 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 173 20%
Researcher 155 17%
Student > Master 79 9%
Student > Bachelor 68 8%
Student > Doctoral Student 53 6%
Other 124 14%
Unknown 235 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 209 24%
Medicine and Dentistry 141 16%
Agricultural and Biological Sciences 72 8%
Neuroscience 35 4%
Computer Science 24 3%
Other 118 13%
Unknown 288 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 34. 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 September 2022.
All research outputs
#1,199,398
of 25,837,817 outputs
Outputs from eLife
#3,685
of 15,816 outputs
Outputs of similar age
#25,572
of 346,471 outputs
Outputs of similar age from eLife
#92
of 337 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,816 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.0. This one has done well, scoring higher than 76% 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 346,471 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 337 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 72% of its contemporaries.