↓ Skip to main content

Citations alone were enough to predict favorable conclusions in reviews of neuraminidase inhibitors

Overview of attention for article published in Journal of Clinical Epidemiology, January 2015
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
7 tweeters

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
26 Mendeley
citeulike
1 CiteULike
Title
Citations alone were enough to predict favorable conclusions in reviews of neuraminidase inhibitors
Published in
Journal of Clinical Epidemiology, January 2015
DOI 10.1016/j.jclinepi.2014.09.014
Pubmed ID
Authors

Xujuan Zhou, Ying Wang, Guy Tsafnat, Enrico Coiera, Florence T. Bourgeois, Adam G. Dunn

Abstract

To examine the use of supervised machine learning to identify biases in evidence selection and determine if citation information can predict favorable conclusions in reviews about neuraminidase inhibitors.

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

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Librarian 5 19%
Unspecified 4 15%
Student > Ph. D. Student 3 12%
Other 3 12%
Student > Postgraduate 2 8%
Other 9 35%
Readers by discipline Count As %
Medicine and Dentistry 6 23%
Unspecified 5 19%
Agricultural and Biological Sciences 5 19%
Social Sciences 5 19%
Computer Science 3 12%
Other 2 8%

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 23 April 2015.
All research outputs
#3,332,975
of 12,340,937 outputs
Outputs from Journal of Clinical Epidemiology
#1,036
of 2,476 outputs
Outputs of similar age
#58,941
of 227,217 outputs
Outputs of similar age from Journal of Clinical Epidemiology
#16
of 36 outputs
Altmetric has tracked 12,340,937 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,476 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has gotten more attention than average, scoring higher than 57% 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 227,217 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 73% of its contemporaries.
We're also able to compare this research output to 36 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 55% of its contemporaries.