# MetaExplorer: Facilitating Reasoning with Epistemic Uncertainty in Meta-analysis

arXiv: https://arxiv.org/abs/2302.04739 · HTML: https://mlsanity.com/paper/2302.04739/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Feb 2023.

## Built on by (most cited first, 1 of 1)

- [Transforming Evidence Synthesis: A Systematic Review of the Evolution of Automated Meta-Analysis in the Age of AI](https://mlsanity.com/paper/2504.20113/) (2025)

## Abstract (arXiv)

Scientists often use meta-analysis to characterize the impact of an intervention on some outcome of interest across a body of literature. However, threats to the utility and validity of meta-analytic estimates arise when scientists average over potentially important variations in context like different research designs. Uncertainty about quality and commensurability of evidence casts doubt on results from meta-analysis, yet existing software tools for meta-analysis do not necessarily emphasize addressing these concerns in their workflows. We present MetaExplorer, a prototype system for meta-analysis that we developed using iterative design with meta-analysis experts to provide a guided process for eliciting assessments of uncertainty and reasoning about how to incorporate them during statistical inference. Our qualitative evaluation of MetaExplorer with experienced meta-analysts shows that imposing a structured workflow both elevates the perceived importance of epistemic concerns and presents opportunities for tools to engage users in dialogue around goals and standards for evidence aggregation.