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Trial2rev: Combining machine learning and crowd-sourcing to create a shared space for updating systematic reviews

Overview of attention for article published in JAMIA Open, January 2019
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)

Mentioned by

twitter
7 tweeters

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
12 Mendeley
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Title
Trial2rev: Combining machine learning and crowd-sourcing to create a shared space for updating systematic reviews
Published in
JAMIA Open, January 2019
DOI 10.1093/jamiaopen/ooy062
Pubmed ID
Authors

Paige Martin, Didi Surian, Rabia Bashir, Florence T Bourgeois, Adam G Dunn

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 33%
Student > Master 2 17%
Researcher 1 8%
Student > Bachelor 1 8%
Unknown 4 33%
Readers by discipline Count As %
Medicine and Dentistry 4 33%
Computer Science 2 17%
Psychology 1 8%
Agricultural and Biological Sciences 1 8%
Unknown 4 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 January 2020.
All research outputs
#4,387,907
of 15,526,154 outputs
Outputs from JAMIA Open
#64
of 132 outputs
Outputs of similar age
#132,557
of 383,866 outputs
Outputs of similar age from JAMIA Open
#1
of 1 outputs
Altmetric has tracked 15,526,154 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 132 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one has gotten more attention than average, scoring higher than 50% 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 383,866 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them