Investigating the impact of weakly supervised data on text mining models of publication transparency: a case study on randomized controlled trials

Lack of large quantities of annotated data is a major barrier in developing effective text mining models of biomedical literature. In this study, we explored weak supervision strategies to improve the accuracy of text classification models developed for assessing methodological transparency of ra…