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# Using Large Language Models to support researchers reproduce and reuse unpublished health care discrete-event simulation computer models: a feasibility and pilot study in Python
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## Authors
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* Thomas Monks [](https://orcid.org/0000-0003-2631-4481)
* Thomas Monks [](https://orcid.org/0000-0003-2631-4481)
The project uses `conda` to manage dependencies. Navigate your terminal to the directory containing the code
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```
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conda env create -f binder/environment.yml
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```
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This will create a conda virtual environment called `gen_simpy`. To activate:
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This will create a conda environment called `gen_simpy`. To activate:
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```
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conda activate gen_simpy
@@ -36,3 +36,17 @@ jb build .
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```
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This will build the HTML book locally on your machine. The terminal will display a URL link that you can use to point your browser at the HTML.
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## Citation
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Please cite this repository as:
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> Thomas Monks, Alison Harper, Amy Heather, and Navonil Mustafee. **Using Large Language Models to support researchers reproduce and reuse unpublished health care discrete-event simulation computer models: a feasibility and pilot study in Python**. <https://github.com/pythonhealthdatascience/llm_simpy>.
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A `CITATION.cff` file is also provided.
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<!--TODO: Archive repository on Zenodo, and cite that -->
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