Given the complexity of the subjects to be represented, however, in the field of life sciences only few scientists with excellent drawing skills (or having access to gifted artists) could successfully and universally propagate their findings using images- think for example of Haeckel’s embryos or of Darwin’s orchids. This is a good example of the conscious usage of a series of images to document a scientific observation and to prove a scientific hypothesis, a common practice in several domains of science. The intent was to prove that the moon surface was rough, with several differences in elevation, in contrast to the idea prevalent at the time of a smooth, perfect sphere. In a set of drawings dating 13th March 1610 published on the “Sidereus Nuncius”, Galileo represented the uneven curve of the sun’s light over the moon disc, as seen only in January of the same year using his telescope 1. The results obtained by these two tests support the feasibility of the software approach and imply an alarming level of image manipulation in the published record. In this paper I introduce a software pipeline to detect some of the most diffuse misbehaviours, running two independent tests on a random set of papers and on the full publishing record of a single journal. With the advent of software for digital image manipulation, however, even photographic reproductions of experimental results may be easily altered by researchers, leading to an increasingly high rate of scientific papers containing unreliable images. In the field of biomedical sciences, in particular, the use of images to depict laboratory results is widely diffused, at such a level that one would not err in saying that there is barely any experimental paper devoid of images to document the attained results. Images in scientific papers are used to support the experimental description and the discussion of the findings since several centuries.
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