Researchers have developed computational tools that not only reveal citation misconduct but also correct the citation errors made.

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Background: All scientists produce reports on their findings, in which they place the work they have done into the context of work conducted by others. Accurate and appropriate citation is at the heart of scientific integrity. However, mis-citations occur, for example as a result of the desire to boost an individual's recognition, harm the reputation of others or simply due to neglect or even innocent oversight. Mis-citations can be incomplete (i.e. missed), inappropriate, and/or erroneous. Such citations, whether intentional or not, can hinder progress in a discipline and may result in revisionist history regarding a scientific milestone. On an individual level, missed citations can be intentionally used to increase the importance and impact of an investigator's work toward enhancing competitiveness for funding and career promotion. Technology: Researchers have developed computational tools that not only reveal citation misconduct but also correct the citation errors made. It is anticipated that the computational approach will reduce bias in grouped-co-citations in manuscripts. Specifically, it is hypothesized that publications are typically quoted together as grouped-co-citations in their respective contexts, and that authors knowingly or accidentally omit appropriate and/or required references. Revealing such occurrences will help reduce the numbers of intentional or accidental omissions and result in better ethics practices for publishing manuscripts. This approach will build on the literature listed in Entrez and should improve all future publications listed in Entrez, which will have positive, far-reaching effects on all fields of biomedical research.  

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