Paper Info
Title
A Synthetic Prediction Market for Estimating Confidence in Published Work.
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.
Year
Venue
Keywords
2022
AAAI Conference on Artificial Intelligence
Prediction Markets,Synthetic Prediction Markets,Feature Extraction,Replication
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
16
Name
Order
Citations
PageRank
Sarah Rajtmajer141.74
Christopher Griffin25811.43
Jian Wu302.37
Robert Fraleigh400.34
Laxmaan Balaji500.34
Anna Cinzia Squicciarini61301106.30
Anthony Kwasnica700.34
David M. Pennock83823451.85
Michael McLaughlin900.34
Timothy Fritton1000.34
Nishanth Nakshatri1100.34
Arjun Menon1200.34
Sai Ajay Modukuri1300.34
Rajal Nivargi1400.34
Xin Wei1500.68
C. Lee Giles16111541549.48