Evaluating Large Language Models for Literature Screening: A Systematic Review of Sensitivity and Workload Reduction
This Zenodo repository provides the supplementary material for the paper titled "Evaluating Large Language Models for Literature Screening: A Systematic Review of Sensitivity and Workload Reduction," [1]. E. Sandner, L. Fontana, K. Kothari, A. Henriques, I. Jakovljevic, A. Simniceanu, A. Wagner and C. Gütl, “Evaluating Large Language Models for Literature Screening: A Systematic Review of Sensitivity and Workload Reduction,” in *Proceedings of the 14th International Conference on Data Science, Technology and Applications (DATA 2025)*, pp. 508–517, 2025, doi: 10.5220/0013562900003967.
Institutions
- World Health Organization - Pakistan (PK)
- Graz University of Technology (AT)
- European Organization for Nuclear Research (CH)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-04-21
- DOI
- https://doi.org/10.5281/zenodo.15255994
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00