  Finding answers related to a pandemic of a novel disease raises new
challenges for information seeking and retrieval, as the new information
becomes available gradually. TREC COVID search track aims to assist in creating
search tools to aid scientists, clinicians, policy makers and others with
similar information needs in finding reliable answers from the scientific
literature. We experiment with different ranking algorithms as part of our
participation in this challenge. We propose a novel method for neural
retrieval, and demonstrate its effectiveness on the TREC COVID search.
