Bias in the reporting of sex and age in biomedical research on mouse models
- Submitting institution
-
The University of Manchester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 50903414
- Type
- D - Journal article
- DOI
-
10.7554/eLife.13615
- Title of journal
- eLife
- Article number
- e13615
- First page
- -
- Volume
- 5
- Issue
- 0
- ISSN
- 2050-084X
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
7
- Research group(s)
-
B - Info, Imag & DS
- Citation count
- 45
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "This paper reports the first use of text analytics to assess the reporting of age and sex of mice used in biomedical experiments, highlighting underlying problems in reproducibility.
Invited Talks:
- SGV meeting (Swiss Laboratory Animal Science Association, 2016)
- Pacific Asia Conference on Language, Information and Computation (2016)
- 2nd Biomedical Linked Annotation Hackathon (BLAH2), (2015);
Enabled PGR to get a job at the National Institute of Health.
Cited by animal research organisations in guidelines to improve research quality (https://www.nc3rs.org.uk/news/does-age-matter)
Media: Nature News, March 2016 (doi:10.1038/nature.2016.19500)"
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
