Researchers spent a large amount of their time searching through an ever increasing number of scientific articles. Although users of scientific search engines prefer the ranking of results according to the number of citations a publication has received, it is never investigated whether this notion of authorativeness could also benefit more traditional and objective measures. Is it also an indicator of relevance, given an information need? In this paper, we examine the relationship between citation features of a scientific article and its prior probability of actually being relevant to some information need. We propose various ways of modeling this relationship and show how this kind of contextual information can be incorporated within a language modeling framework. We experiment with three document priors, which we evaluate on three distinct sets of queries and two document collections from the TREC Genomics track. Empirical results show that two of the proposed priors can significant...