In-depth analysis of ChatGPT’s performance based on specific signaling words and phrases in the question stem of 2377 USMLE step 1 style questions
- DOI
- 10.1038/s41598-024-63997-7
- Published
- 2024-06-12
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-024-63997-7,
title = {In-depth analysis of ChatGPT’s performance based on specific signaling words and phrases in the question stem of 2377 USMLE step 1 style questions},
author = {Leonard Knoedler and Samuel Knoedler and Cosima C. Hoch and Lukas Prantl and Konstantin Frank and Laura Soiderer and Sebastian Cotofana and Amir H. Dorafshar and Thilo Schenck and Felix Vollbach and Giuseppe Sofo and Michael Alfertshofer},
year = {2024},
journal = {Scientific Reports},
doi = {10.1038/s41598-024-63997-7},
url = {https://doi.org/10.1038/s41598-024-63997-7}
}RIS
TY - JOUR TI - In-depth analysis of ChatGPT’s performance based on specific signaling words and phrases in the question stem of 2377 USMLE step 1 style questions AU - Leonard Knoedler AU - Samuel Knoedler AU - Cosima C. Hoch AU - Lukas Prantl AU - Konstantin Frank AU - Laura Soiderer AU - Sebastian Cotofana AU - Amir H. Dorafshar AU - Thilo Schenck AU - Felix Vollbach AU - Giuseppe Sofo AU - Michael Alfertshofer PY - 2024 JO - Scientific Reports DO - 10.1038/s41598-024-63997-7 UR - https://doi.org/10.1038/s41598-024-63997-7 ER -
APA
Knoedler, L., Knoedler, S., Hoch, C. C., Prantl, L., Frank, K., Soiderer, L., Cotofana, S., Dorafshar, A. H., Schenck, T., Vollbach, F., Sofo, G., & Alfertshofer, M. (2024). In-depth analysis of ChatGPT’s performance based on specific signaling words and phrases in the question stem of 2377 USMLE step 1 style questions. Scientific Reports. https://doi.org/10.1038/s41598-024-63997-7
Source records
- crossref · retrieved 2026-09-26T07:19:42.727Z