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Bik et al. (2016) - The Prevalence of Inappropriate Image Duplication in Biomedical Research Publications
webmbio.asm.org·mbio.asm.org/content/7/3/e00809-16
Relevant to AI safety discussions around benchmarking and evaluation integrity; demonstrates systemic vulnerabilities in scientific publishing that parallel concerns about trustworthiness of AI research results and capability evaluations.
Metadata
Importance: 42/100journal articleprimary source
Summary
This large-scale study screened over 20,000 papers across 40 scientific journals and found that 3.8% contained problematic figures with inappropriate image duplication, at least half showing signs of deliberate manipulation. The prevalence has risen markedly over the past decade, and journal-level practices like prepublication image screening appear to influence data quality.
Key Points
- •3.8% of 20,621 screened papers contained problematic figures, with at least half suggestive of deliberate manipulation rather than honest error
- •Prevalence of papers with problematic images has risen markedly during the decade from 1995-2014
- •Authors who had one problematic paper were more likely to have additional problematic papers, suggesting repeat offenders
- •Journal-level practices such as prepublication image screening significantly influence the quality of published literature
- •Analysis covered only image duplication, so actual prevalence of inaccurate data in the literature is likely higher
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| Scientific Knowledge Corruption | Risk | 91.0 |
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Contents
## ABSTRACT
Inaccurate data in scientific papers can result from honest error or intentional falsification. This study attempted to determine the percentage of published papers that contain inappropriate image duplication, a specific type of inaccurate data. The images from a total of 20,621 papers published in 40 scientific journals from 1995 to 2014 were visually screened. Overall, 3.8% of published papers contained problematic figures, with at least half exhibiting features suggestive of deliberate manipulation. The prevalence of papers with problematic images has risen markedly during the past decade. Additional papers written by authors of papers with problematic images had an increased likelihood of containing problematic images as well. As this analysis focused only on one type of data, it is likely that the actual prevalence of inaccurate data in the published literature is higher. The marked variation in the frequency of problematic images among journals suggests that journal practices, such as prepublication image screening, influence the quality of the scientific literature.
## INTRODUCTION
Inaccuracies in scientific papers have many causes. Some result from honest mistakes, such as incorrect calculations, use of the wrong reagent, or improper methodology ( [1](https://journals.asm.org/doi/10.1128/mbio.00809-16#B1)). Others are intentional and constitute research misconduct, including situations in which data are altered, omitted, manufactured, or misrepresented in a way that fits a desired outcome. The prevalence rates of honest error and misconduct in the scientific literature are unknown. One review estimated the overall frequency of serious research misconduct, including plagiarism, to be 1% ( [2](https://journals.asm.org/doi/10.1128/mbio.00809-16#B2)). A meta-analysis by Fanelli, combining the results of 18 publ
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