RES: An Interpretable Replicability Estimation System for Research Publications

نویسندگان

چکیده

Reliable and faithful research is the cornerstone of breakthrough advancements disruptive innovations. Assessing credibility scientific findings claims in publications has long been a time-consuming challenging task for researchers decision-makers. In this paper, we introduce RES - an intelligent system that assists humans analyzing field social behavioral sciences by estimating their replicability. The pipeline consists four major modules perform feature extraction, replicability estimation, result explanation, sentiment analysis respectively. Our evaluation based on human experts' assessments suggests achieved adequate performance. also built with Graphical User Interface (GUI) publicly accessible at https://tamu-infolab.github.io/RES/.

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ژورنال

عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence

سال: 2022

ISSN: ['2159-5399', '2374-3468']

DOI: https://doi.org/10.1609/aaai.v36i11.21737