Using Llama to summarize PubMed Central (PMC) full text articles that contain information on protein function

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

2025-04 (month precision)Source: Apr-25

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Science

Operational functions

Summarization Derived by keyword rules; see methodology

Problem the AI is intended to solve

Inefficient and manual process to assign accurate function to proteins and protein models

Expected benefits

This will increase efficiency of curators’ work in providing up-to-date functional annotation for prokaryotic protein family models for use in the annotation pipeline and in adding this to RefSeq proteins.

System outputs

Article summaries

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

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

Not reported

Authorization to Operate

No

Demographic features

k) None of the above

Training and evaluation data

PMC data

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.

Potential impacts and how they were identified

Not reported