![]() ![]() Google T5 (model card t5-large) with settings from GitHub was used to summarize the abstracts. To generate the summaries, AI² SCITLDR website was used with abstract, introduction and discussion. The AI-generated text has not been modified, so does not conform to Nature’s usual editorial standards for grammar and style. ![]() We then show a paper summary by the Allen Institute for Artificial Intelligence’s (AI²) SCITLDR, based on the original abstract, introduction and discussion, and summaries of the paper’s introduction and discussion by SciBERT using a summary ratio of 0.3. They are also open access.įor each we present the authors’ original abstract and summaries of it made by two abstractive summarization approaches, Google’s T5 and Pegasus. Using three articles from Nature Communications with a consistent format allows for more direct comparisons between the auto-generated text. 33, 71–82 2019) for the sake of consistency and ease of access. We elected to present it instead of the most highly-cited article ( D. was the second-most highly cited article in the data set. ![]() Two of the articles featured ranked highest in the data set on objective metrics for either downloads (Mendez-Lucio et al.) or social media attention by Altmetric score (Piazza et al.). Nature Index 2020 Artificial intelligence (Digital Science is a subsidiary of Holtzbrinck Publishing Group, which owns 53% of Springer Nature, publisher of the Nature Index.) The results were then filtered according to Springer Nature’s article classification model for article type ‘original paper’ and ‘research article’ and exported from Digital Science’s Dimensions database on 14 October 2020. The data set was derived using the title and abstract search ‘(‘artificial intelligence’ OR ‘AI’ OR ‘machine learning’ OR ‘deep learning’) AND (‘drug discovery’ OR ‘drug design’)’ in Publication Year 2020 or 2019. We present AI-generated summaries of three articles selected from a data set of 175 Springer Nature publications in 20. Summarize 3rd chunk + 1st and 2nd chunk summary.The network connects co-occurring terms in 175 articles published by Springer Nature related to using AI in drug discovery.
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