Save embeddings and articles into their corresponding folders: ex) for pmc embeddings, save PMC_Abs_Embeds.npy, PMC_Main_Embeds.npy in embeddings/pmc

Navigate to the directory where main.py is located.

Execute the Python script main.py using the following command:

For PubMed, we grouped the 38 chunks into 10, 10, 10, and 8 subgroups, respectively. We retrieved 10 evidences from each subgroup using MIPS, totaling 40 evidences. For PMC, CPG, and textbook, we retrieved 10 evidences from each. With a total of 70 evidences, we reranked them and obtained the final 10 evidences. The number of PubMed subgroup chunks can be adjusted using the --pubmed_group_num argument.

We used SciSpacy en_core_sci_scibert to add [SEP] tokens for encoding queries and articles for MIPS but not for the reranker following MEDCPT (Jin et al., 2023). This functionality is optional and can be enabled using the --use_spacy argument.