Automatically classify QA comments by type and severity

When a measure package is being reviewed, use AI to automatically classify comments into severity levels (High/Medium/Low) and comment category. This will enable quicker reviews by helping prioritize and respond to QA comments.

Example categories:

CriticalityBroad CategorySpecific Category

High Criticality

Savings

Savings: methods, assumptions, base/measure, or data

High Criticality

Savings

Savings: general/issue with results

High Criticality

Costs

Costs: methods/assumptions/data

High Criticality

Costs

Costs: general/issue with results

High Criticality

Permutation edit

Permutation edit: add Tech ID

High Criticality

Permutation edit

Permutation edit: MAT

High Criticality

NTG

Update NTG

Medium Criticality

Methodology description

Methodology description: incomplete/unclear/missing/erroneous

Medium Criticality

Clarification needed

Clarification needed: technical/code/program

Medium Criticality

Analysis reference

Analysis reference: incomplete/unclear/missing

Medium Criticality

Future comment

Future comment: will be high criticality in the future

Low Criticality

Language update

grammar, spelling, and suggested clarity

Low Criticality

Comment out of scope

Comment out of scope: comment on wrong version

Low Criticality

Comment out of scope

Comment out of scope: general comment to PA

Low Criticality

Comment out of scope

Comment out of scope: reporting and EM&V processes outside the eTRM

Low Criticality

Code information

Code information: date, cycle number, and/or reference

Low Criticality

Reference Edit

Reference edit

Low Criticality

Delivery type

Delivery type: midstream/upstream

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Upvoters
Status

In Review

Board
πŸ’‘

Feature Request

Tags

AI Integration

Date

2 months ago

Author

GrantB

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