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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RevManHAL: towards automatic text generation in systematic reviews
|
|---|---|
| Published in |
Systematic Reviews, February 2017
|
| DOI | 10.1186/s13643-017-0421-y |
| Pubmed ID | |
| Authors |
Mercedes Torres Torres, Clive E. Adams |
| Abstract |
Systematic reviews are a key part of healthcare evaluation. They involve important painstaking but repetitive work. A major producer of systematic reviews, the Cochrane Collaboration, employs Review Manager (RevMan) programme-a software which assists reviewers and produces XML-structured files. This paper describes an add-on programme (RevManHAL) which helps auto-generate the abstract, results and discussion sections of RevMan-generated reviews in multiple languages. The paper also describes future developments for RevManHAL. RevManHAL was created in Java using NetBeans by a programmer working full time for 2 months. The resulting open-source programme uses editable phrase banks to envelop text/numbers from within the prepared RevMan file in formatted readable text of a chosen language. In this way, considerable parts of the review's 'abstract', 'results' and 'discussion' sections are created and a phrase added to 'acknowledgements'. RevManHAL's output needs to be checked by reviewers, but already, from our experience within the Cochrane Schizophrenia Group (200 maintained reviews, 900 reviewers), RevManHAL has saved much time which is better employed thinking about the meaning of the data rather than restating them. Many more functions will become possible as review writing becomes increasingly automated. |
X Demographics
The data shown below were collected from the profiles of 43 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 | 11 | 26% |
| United States | 4 | 9% |
| Canada | 3 | 7% |
| Australia | 2 | 5% |
| Norway | 1 | 2% |
| Austria | 1 | 2% |
| Italy | 1 | 2% |
| Yemen | 1 | 2% |
| El Salvador | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 16 | 37% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 21 | 49% |
| Scientists | 12 | 28% |
| Practitioners (doctors, other healthcare professionals) | 7 | 16% |
| Science communicators (journalists, bloggers, editors) | 3 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 47 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 17% |
| Student > Ph. D. Student | 6 | 13% |
| Student > Master | 6 | 13% |
| Student > Doctoral Student | 3 | 6% |
| Student > Bachelor | 3 | 6% |
| Other | 9 | 19% |
| Unknown | 12 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 26% |
| Computer Science | 5 | 11% |
| Nursing and Health Professions | 5 | 11% |
| Psychology | 3 | 6% |
| Engineering | 2 | 4% |
| Other | 5 | 11% |
| Unknown | 15 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 28. 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 04 April 2019.
All research outputs
#1,386,467
of 25,595,500 outputs
Outputs from Systematic Reviews
#202
of 2,242 outputs
Outputs of similar age
#29,213
of 425,805 outputs
Outputs of similar age from Systematic Reviews
#10
of 50 outputs
Altmetric has tracked 25,595,500 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,242 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 91% 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 425,805 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 93% of its contemporaries.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.