HHS · no agency ID · record R0943

Study Section Clustering Tool (SSCT)

Department of Health and Human Services · HHS/NIH

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Overview

Development stage: DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2023-01 (month precision)Source: Jan-23
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Administrative Functions
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Efficiently organizing grant applications into appropriate study sections based on scientific similarity.

Expected benefits

The Study Section Clustering Tool (SSCT) enhances the agency’s mission by automating and streamlining the organization of grant applications into scientifically relevant study sections, improving efficiency and reducing manual effort. It ensures applications are reviewed by experts with appropriate expertise, adapting over time to changes in scientific fields through periodic model updates. This data-driven support leads to higher-quality peer review processes, promoting more effective research funding decisions

System outputs

The AI system’s outputs are lists of study sections grouped together based on the scientific similarity of grant application texts. Specifically, it generates clusters of applications that should be reviewed collectively because they share related scientific topics. These groupings serve as recommendations to subject matter experts, who use them to finalize the organization of study sections for peer review panels.

Technology

AI classification: Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
System name(s): Center for Scientific Review General Support System (CSR GSS)
Custom-developed code: Yes
Public source code: NO

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: It does not have a standalone publicly available Privacy Impact Assessment (PIA). However, it operates within the Center for Scientific Review General Support System (CSR GSS), which is a FISMA-reportable system that has an associated PIA covering the overall system environment where the AI tool functions.
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: text of grant applications submitted to the Center for Scientific Review (CSR).
Federal Data Catalog: not publicly disclosed as an open government data asset

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported