This paper presents the preliminary results of an ongoing project that analyzes the growing body of scientific research published around the COVID-19 pandemic. In this research, a general-purpose semantic model is used to double annotate a batch of 500 sentences that were manually selected from the CORD-19 corpus. Afterwards, a baseline text-mining pipeline is designed and evaluated via a large batch of 100, 959 sentences. We present a qualitative analysis of the most interesting facts automatically extracted and highlight possible future lines of development. The preliminary results show that general-purpose semantic models are a useful tool for discovering fine-grained knowledge in large corpora of scientific documents.1 https://www.kaggle.com/ allen-institute-for-ai/ CORD-19-research-challenge Phylogenetic studies have shown that 2019-nCoV and SARS-CoV belong to the subgenus Sarbecovirus, but they are distantly related 5-8 , with a sequence identity of 79.6% at the whole-genome level 5 However, SARS-CoV, using the same receptor, was not detected in skeletal muscle by post-mortem examinationIn conclusion, SARS-Cov is the closest related virus to 2019-nCoV for which a significant number of epitopes has been defined in humans (and other species), and that also causes human disease with lethal outcomes Concept Concept Concept ,, Action Concept Con Concept

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