A Synthetic Prediction Market for Estimating Confidence in Published Work

Authors

  • Sarah Rajtmajer The Pennsylvania State University
  • Christopher Griffin The Pennsylvania State University
  • Jian Wu Old Dominion University
  • Robert Fraleigh The Pennsylvania State University
  • Laxmaan Balaji The Pennsylvania State University
  • Anna Squicciarini The Pennsylvania State University
  • Anthony Kwasnica The Pennsylvania State University
  • David Pennock Rutgers University
  • Michael McLaughlin The Pennsylvania State University
  • Timothy Fritton The Pennsylvania State University
  • Nishanth Nakshatri The Pennsylvania State University
  • Arjun Menon The Pennsylvania State University
  • Sai Ajay Modukuri The Pennsylvania State University
  • Rajal Nivargi The Pennsylvania State University
  • Xin Wei Old Dominion University
  • C. Lee Giles The Pennsylvania State University

DOI:

https://doi.org/10.1609/aaai.v36i11.21733

Keywords:

Prediction Markets, Synthetic Prediction Markets, Feature Extraction, Replication

Abstract

Explainably estimating confidence in published scholarly work offers opportunity for faster and more robust scientific progress. We develop a synthetic prediction market to assess the credibility of published claims in the social and behavioral sciences literature. We demonstrate our system and detail our findings using a collection of known replication projects. We suggest that this work lays the foundation for a research agenda that creatively uses AI for peer review.
AAAI-22 Proceedings Cover

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Published

2022-06-28

How to Cite

Rajtmajer, S., Griffin, C., Wu, J., Fraleigh, R., Balaji, L., Squicciarini, A., Kwasnica, A., Pennock, D., McLaughlin, M., Fritton, T., Nakshatri, N., Menon, A., Modukuri, S. A., Nivargi, R., Wei, X., & Giles, C. L. (2022). A Synthetic Prediction Market for Estimating Confidence in Published Work. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13218-13220. https://doi.org/10.1609/aaai.v36i11.21733

Issue

Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Section

AAAI Demonstration Track