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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Citations alone were enough to predict favorable conclusions in reviews of neuraminidase inhibitors
|
|---|---|
| Published in |
Journal of Clinical Epidemiology, October 2014
|
| 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. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 3 | 38% |
| United Kingdom | 2 | 25% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 50% |
| Members of the public | 2 | 25% |
| Practitioners (doctors, other healthcare professionals) | 2 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Unknown | 49 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 14% |
| Librarian | 5 | 10% |
| Student > Master | 5 | 10% |
| Student > Bachelor | 5 | 10% |
| Other | 3 | 6% |
| Other | 11 | 22% |
| Unknown | 14 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 22% |
| Social Sciences | 9 | 18% |
| Agricultural and Biological Sciences | 5 | 10% |
| Computer Science | 5 | 10% |
| Nursing and Health Professions | 2 | 4% |
| Other | 2 | 4% |
| Unknown | 16 | 32% |
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
#7,356,550
of 25,374,917 outputs
Outputs from Journal of Clinical Epidemiology
#2,434
of 4,783 outputs
Outputs of similar age
#76,118
of 273,237 outputs
Outputs of similar age from Journal of Clinical Epidemiology
#19
of 45 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 4,783 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.1. This one is in the 47th percentile – i.e., 47% 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 273,237 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 70% of its contemporaries.
We're also able to compare this research output to 45 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.