Summary/Abstract
The research showcases a comprehensive machine-learning-assisted evidence map that utilizes natural language processing (NLP) to process large volumes of climate-related studies. This method allows for the efficient organization and categorization of the vast amount of data, identifying where human-induced climate impacts are most likely occurring. The study discusses the methodology in detail, including the challenges of managing such large data sets and the potential biases in the distribution of research focus worldwide.