# Explanation Container in Case-Based Biomedical Question-Answering

Source: [Explanation Container in Case-Based Biomedical Question-Answering](<https://www.sota2.com/research/paper/68fa6b781e209131cea2e564>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:56:51.063Z

Authors: Prateek Goel, Adam J. Johs, Manil Shrestha, Rosina O. Weber

Published: 2021-12-13T16:44:27.000Z

## Abstract

The National Center for Advancing Translational Sciences(NCATS) Biomedical Data Translator (Translator) aims to attenuate problems faced by translational scientists. Translator is a multi-agent architecture consisting of six autonomous relay agents (ARAs) and eight knowledge providers (KPs). In this paper, we present the design of the Explanatory Agent (xARA), a case-based ARA that answers biomedical queries by accessing multiple KPs, ranking results, and explaining the ranking of results. The Explanatory Agent is designed with five knowledge containers that include the four original knowledge containers and one additional container for explanation - the Explanation Container. The Explanation Container is case-based and designed with its own knowledge containers.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2112.06780>)

[PDF](<https://arxiv.org/pdf/2112.06780.pdf>)