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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error
|
|---|---|
| Published in |
Systematic Reviews, January 2019
|
| DOI | 10.1186/s13643-019-0942-7 |
| Pubmed ID | |
| Authors |
Alexandra Bannach-Brown, Piotr Przybyła, James Thomas, Andrew S. C. Rice, Sophia Ananiadou, Jing Liao, Malcolm Robert Macleod |
X Demographics
The data shown below were collected from the profiles of 63 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 17 | 27% |
| United States | 6 | 10% |
| Netherlands | 4 | 6% |
| Australia | 3 | 5% |
| Switzerland | 2 | 3% |
| Norway | 1 | 2% |
| Canada | 1 | 2% |
| Korea, Republic of | 1 | 2% |
| Belgium | 1 | 2% |
| Other | 5 | 8% |
| Unknown | 22 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 36 | 57% |
| Scientists | 19 | 30% |
| Practitioners (doctors, other healthcare professionals) | 5 | 8% |
| Science communicators (journalists, bloggers, editors) | 3 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 251 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 251 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 39 | 16% |
| Student > Master | 35 | 14% |
| Student > Bachelor | 27 | 11% |
| Researcher | 25 | 10% |
| Student > Doctoral Student | 8 | 3% |
| Other | 39 | 16% |
| Unknown | 78 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 33 | 13% |
| Medicine and Dentistry | 28 | 11% |
| Agricultural and Biological Sciences | 15 | 6% |
| Engineering | 12 | 5% |
| Psychology | 11 | 4% |
| Other | 59 | 24% |
| Unknown | 93 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 41. 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 02 February 2022.
All research outputs
#1,025,187
of 25,709,917 outputs
Outputs from Systematic Reviews
#133
of 2,247 outputs
Outputs of similar age
#24,593
of 466,328 outputs
Outputs of similar age from Systematic Reviews
#7
of 93 outputs
Altmetric has tracked 25,709,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,247 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.2. This one has done particularly well, scoring higher than 94% 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 466,328 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 94% of its contemporaries.
We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.