This repository contains baseline experiments from the paper "CSMeD: Bridging the Dataset Gap in Automated Citation Screening for Systematic Literature Reviews". CSMeD dataset is described and available at: WojciechKusa/systematic-review-datasets.

Tested with Python 3.10.

Assuming you have conda installed, run:

$ conda create -n csmed python=3.10
$ conda activate csmed
(csmed)$ pip install -r requirements.txt

To run the experiments on CSMeD-Cochrane, run:

(csmed)$ python experiments/csmed_cochrane/csmed_cochrane_retrieval.py

Results of the baseline experiment are available under the following URL csmed-cochrane-baseline-results.zip

Experiments on CSMeD-FT consist of two parts: (1) fine-tuned classification Transformer models and (2) zero-shot prompting via OpenAI models.

To run the classification experiments, run:

(csmed)$ python experiments/csmed_ft/full_text_classification.py

To run the zero-shot prompting experiments, run:

(csmed)$ python experiments/csmed_ft/full_text_prompting.py