HHS · no agency ID · record R0668

School LLM initial abstract review process

Department of Health and Human Services · HHS/CDC

Overview

Development stage: PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2023-08 (month precision)Source: Aug-23
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Administrative Functions
Operational functions: Document processing and extraction Derived by keyword rules; see methodology

Problem the AI is intended to solve

Manual review and categorization of thousands of research abstracts related to school readiness science is time-consuming. The AI enables efficient extraction and categorization of themes, reducing human effort and time.

Expected benefits

The AI allows for efficient categorization of thousands of abstracts in a much shorter time frame, with less human effort, and presents results in a user-friendly dashboard for health scientists to use in research and decision-making.

System outputs

The AI uses an LLM to extract data from abstract reviews and categorize relevant themes and topics into a user-friendly dashboard, enabling users to pull resources from 2012–2022 for specific school closure outcomes or themes.

Technology

AI classification: Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
System name(s): Not reported
Custom-developed code: No
Public source code: Not reported

Sourcing

How it was built: Contract and in-houseSource: c) Developed with both contracting and in-house resources
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: Not reported
Authorization to Operate: No
Demographic features: k) None of the above
Training and evaluation data: Not reported
Federal Data Catalog: Not reported

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