Research Compendium: Replicating Simulations in Python using Generative AI

This repository serves as a research compendium for the paper:

Monks, T., Harper, A., & Heather, A. (2025). Unlocking the Potential of Past Research: Using Generative AI to Reconstruct Healthcare Simulation Models.

A research compendium is collection of all the digital materials relevant to the study. In this case, it includes a description of the aims and models, as well the STRESS reports for each model, the full model code and testing, logs of all the prompts used and experiences working with the LLMs, analysis of the results, and more!

🌱 v0.1.0

Full research compendium released.

Added

• Repository essentials: CHANGELOG, CITATION, README, binder/environment.yml
• Full research compendium to accompany: Monks T, Harper A, and Heather A. (2025): Unlocking the Potential of Past Research: Using Generative AI to Reconstruct Healthcare Simulation Models. Preprint
• The compendium contains
  • the Python code, simpy models, and documentation generated by Perplexity.AI
  • All prompts from stages 1 and 2 of the study
• The compendium can be compiled into a JupyterBook website.