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llm-guardrails

Data from the LLM Guardrails experiment used to support the article below:

The Need for Guardrails with Large Language Models in Medical Safety-Critical Settings: An Artificial Intelligence Application in the Pharmacovigilance Ecosystem

https://arxiv.org/abs/2407.18322

Data Evaluation for Publication Support

Folder structure

  • data : Contains final redacted datasets from Phase 1 and 2 of our LLM experiment

Data File Descriptions

LLM-Phase 1 Export

data/llmphase1_final_review.csv The source and translation fields have been redacted for github storage

This file contains the following fields:

Data Fields

  • ReviewID : Auto-generated database key
  • Case Master ID : Unique Case ID
  • Case Date : Initial receipt date of the case
  • Reviewer_1 : username of first reviewer
  • Reviewer_1_Time : time (in miliseconds) of first reviewer
  • Reviewer_2 : username of second reviewer (should not equal first reviewer)
  • Reviewer_2_Time : time (in miliseconds) of second reviewer
  • ExamplePost : Reviewer felt this was a good post to be highlighted to the team
  • Secondary: Source is clear
  • Correct assessment?
  • Translation accuracy
  • Source has multiple meanings
  • Source is clear
  • Source contains contradictions

LLM-Phase 2 Export

Cases that have been completely reviewed should have at minimum (2) row entries (matching on Case master ID). Each case was imported into the database and (2) copies were made to insure each case is reviewed twice. The business logic prevents the same user from being presented the same Case Master ID twice. If a case goes through two reviews and the reviewers fail to agree, it is flagged for adjudciation and a 3rd party will review. In that case, there will be a 3rd copy of the case made, the fields were each reviewer agreed will automatically be populated for the adjudicator's case review. The adjudicator is then forced to make a decision on the fields where the reviewers disagreed.

Cases that did not require adjudcation and have 2 reviews completed are then eligible for QC review. QC review is a randomly selected process, and the QC process again creates a 3rd copy of the case. All fields are duplicated for the QC reviewer, and they have an opportunity to make changes or updates only to their QC version of the case review.

data/llmphase2_final_review.csv

These files contain the following fields.

Data Fields

  • ReviewID : Auto-generated database key
  • Case Master ID : Unique Case ID
  • QC Case Review : True if this was a QC review of the case
  • Adjudicated Case : True if this was the adjudicator's review of the case
  • Case differences : When a case has been submitted as the second time in review, a count of differences between reviewers is calculated and stored here
  • Case Date : Initial receipt date of the case
  • Reviewer_1 : Single reviewer per case. For each Case Master ID, this should not be duplicated (require 2 different reviewers)
  • Reviewer_1_Time : time (in miliseconds) of case reviewer
  • Is Original Narartive clear? : Ranking question scale 1-5
  • Is LLM Narartive clear? : Ranking question scale 1-5
  • Source contains contradictions : Yes/No Question
  • LLM contains contradictions : Yes/No Question
  • Good example case? : Yes/No Question
  • Completeness of LLM text : Ranking question scale 1-5
  • Correctness of LLM text : Ranking question scale 1-5
  • Amount of extaneous information auxillary (not drug safety related) in translated text : Ranking question scale 1-5
  • Amount of key* (drug safety related) information in the translation not present in the source text : Ranking question scale 1-5
  • Wrong Drug name or information : Yes/No Question
  • Wrong Dosage : Yes/No Question
  • Wrong Dates/times : Yes/No Question
  • Incorrect/missing AE/Wrong Outcome : Yes/No Question
  • Rechallenge/dechallenge : Yes/No Question
  • TTO issues : Yes/No Question
  • Non-sensical Phrases : Yes/No Question
  • Other Errors : Yes/No Question
  • Is the case clinically accurate? : Yes/No Question

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Data from our LLM Guardrails experiment

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