The late precambrian avalonian orogeny in avalon, southeast newfoundland

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ID: 297974
1970
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Abstract

Abstract

Scientific fraud by image duplications and manipulations within western blot images is a rising problem. Currently, problematic western blot images are mainly detected by checking repeated bands or through visual observation. However, the completeness of the above methods in detecting problematic images has not been demonstrated. Here we show that Generative Adversarial Nets (GANs) can generate realistic western blot images that indistinguishable from real western blots. The overall accuracy of researchers for identifying synthetic western blot images is 0.52, which almost equal to blind guess (0.5). We found that GANs can generate western blot images with bands of the expected lengths, widths, and angles in desired positions that can fool researchers. For the case study, we find that the accuracy of detecting the synthetic western blot images is related to years of researchers performed studies relevant to western blots, but there was no apparent difference in accuracy among researchers with different academic degrees. Our results demonstrate that GANs can generate fake western blot images to fool existing problematic image detection methods. Therefore, more information is needed to ensure that the western blots appearing in scientific articles are real. We argue to require every western blot image to be uploaded along with a unique identifier generated by the laboratory machine and to peer review these images along with the corresponding submitted articles, which may reduce the incidence of scientific fraud.
Reference Key
openalex_W2317654553 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors C. J. Hughes
Journal american journal of science
Year 1970
DOI
10.2475/ajs.269.2.183
URL
https://ajs.scholasticahq.com/article/59401.pdf
Keywords Keywords not found

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