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Leaving aside such individual and often spectacular cases that have been uncovered, the total number of image manipulations in submitted scientific papers remains unknown and can only be estimated, e.g. by online surveys among scientists. According to such a survey by Martinson et al., 0.3% of 3247 scientists admitted to having “cooked” or falsified research data themselves. About 15% said that they had previously engaged in behaviors such as “dropping observations or data points”, and 4.7% admitted to reusing data in two or more publications (Martinson et al. 2005 ) (the survey did not explicitly ask about image manipulation). Recently, based on a visual (“by eye”) screening of 20,621 papers in 40 scientific journals, a group of US-researchers estimated the prevalence of the specific case of inappropriate image duplication at 3.8%, with an increasing tendency during the past decade (Bik et al. 2016 ). This is in line with the observation that in biomedical literature, the number of retractions has increased in the last few years, in many cases due to manipulated images (Krueger 2012 ). As efficient and systematic screening of image manipulation is not yet available, it can only be assumed that the technical (software) possibilities of image editing may have increased the probability of image manipulation.

Spectacular cases of fraud with broader media attention refuel the debate on how such manipulation could have been avoided and who will be responsible for better quality control in the future. Journal editors have recognized this problem and organized in the “Committee on publication ethics” (COPE, http://publicationethics.org ). However, journals such as the Journal of Cell Biology controlling systematically images are rather regarded as an exception (Couzin 2006b ). Responsible editors usually point out reviewers’ and editors’ limited possibilities, as did Donald Kennedy, former editor-in-chief at Science: “Peer review cannot detect [fraud] if it is artfully done. (…) And the reported falsifications in the Hwang paper—image manipulation and fake DNA data—are not the sort that reviewers can easily spot” (Couzin 2006a ). Concerning the above-mentioned case of oncologist Jon Sudbø, Richard Horton, editor of The Lancet, claimed: “This is all so similar to the Hwang thing that we have just been through. (…) Peer review is a great system for detecting badly done research, but if you have an investigator determined to fabricate an entire study, it is not possible to pick it up” (Butler 2006 ). Even clearly fabricated papers have a good chance to be accepted, as John Bohannon showed in an experiment with free access journals (Bohannon 2013 ).

These statements seem to still be true today, at least for more sophisticated manipulations that are undetectable by the bare eye, or for manipulations obviously violating established guidelines such as Nature Journal’s guidelines for “Image integrity and standards” (Nature Buy Cheap Nicekicks Cheap Sale Footlocker Finishline Christian Louboutin Pigalle Follies PointedToe Pumps Discount Pre Order d6KC8V
). Such guidelines provide some orientation to which degree an image may still be regarded as authentic after electronic corrections to brightness, contrast etc. To our knowledge, there is still a lack of widely spread and standardized screening methods for reviewers or editors to routinely verify the authenticity of a submitted scientific image. In principle, such screening tools would be useful for everybody involved in the process of quality control. However, journal editors, in particular, should have a choice from a variety of different methods because falsifiers, who also have access to any given screening tool on the free market, will eventually learn to mask their manipulations and render them undetectable by this specific screening tool.

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