Résumé
Scientific discourse on the social web has been shown to compromise the accuracy of scientific findings. Complex scientific claims are uttered in the form of short snippets with "implicit references" (seen as references to scientific publications where the URLs to the actual studies are never cited). This has led to uninformed online scientific debates on topics such as health pandemics or climate. To enhance social media content, we introduce in this paper the novel task of disambiguation of implicit scientific references, where the goal is to retrieve the original scientific publications implicitly referred to by social media users. We contribute the first formalization, ground-truth corpus, and baselines for the task. With this work, we aim at shaping an understanding of implicit references on social media, and at laying a foundation for developing and evaluating methods for the disambiguation of implicit references.