Assessing the reach and impact of natural history collections requires reviewing scientific literature for citations to specimens, which can be labor-intensive. This project curates and analyzes a bibliography of literature citing specimens from the University of Michigan Museum of Zoology. We demonstrate a machine learning approach we are developing to detect specimen citations in scientific literature with the goal of enabling comprehensive studies of specimen reuse patterns across multiple natural history collections. This poster was presented at the 2022 July ESIP Meeting in Pittsburgh, PA.