Technical Supplement to the Medical Education Corpus
These files comprise the technical supplement to the Medical Education Corpus (MEC), the first dedicated collection of medical education papers. Included is the technical supplement, which outlines — in brief but complete detail — all the steps taken to develop and evaluate the MEC Classifier. The MEC Classifier is a machine learning model that was used to create the MEC. There is also journal data (Medical Education Journals, consisting of MEJ-Core and MEJ-Adjacent), all labeled papers used to train the MEC Classifier, the final created MEC, along with a minimal code implementation in mec_code.py. The code file is MIT licensed. The remaining files including the dataset files and the technical supplement are licensed under CC-BY. ===== 20250324 Revision - An issue was found by Joe Costello where there were duplicate entires in Supplement 4, the MEC Papers. This issue was traced back to the code that outputted Supplement 4 as a CSV. This bug was fixed and Supplement 4 was regenerated, now without duplicates.
Institutions
- University of California, San Francisco (US)
- George Washington University (US)
- University of Illinois Chicago (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-03-24
- DOI
- https://doi.org/10.5281/zenodo.15077560
- Primary Topic
- RNA Research and Splicing
- Type
- article
- Field-Weighted Citation Impact
- 0.00