MOESM4 of Use of literature mining for early identification of emerging contaminants in freshwater resources Julia Hartmann Susanne Wuijts Jan Hoek Ana Roda Husman 10.6084/m9.figshare.9975734.v1 https://springernature.figshare.com/articles/dataset/MOESM4_of_Use_of_literature_mining_for_early_identification_of_emerging_contaminants_in_freshwater_resources/9975734 Additional file 4. Analysis for false negatives of random selection of 1750 articles from the 23,217 articles (published between 2006 and 2012) that did not match the pattern. Table containing the articles’ Electronic Identifier (EID), authors, title, publication year, journal, volume, page information, citations, Digital Object Identifier (DOI), link to the article in Scopus®, abstract, the sentence that matched the pattern and whether the articles is considered to be a false negative or not. 2019-10-14 04:18:33 Chemical Microbial emerging pathogen Text mining R-based Early warning Water Health Emergence