Zero-Shot Generative Large Language Models for Systematic Review Screening Automation

Author:

Wang ShuaiORCID,Scells HarrisenORCID,Zhuang ShengyaoORCID,Potthast MartinORCID,Koopman BevanORCID,Zuccon GuidoORCID

Publisher

Springer Nature Switzerland

Reference65 articles.

1. Abualsaud, M., Ghelani, N., Zhang, H., Smucker, M.D., Cormack, G.V., Grossman, M.R.: A system for efficient high-recall retrieval. In: Proceedings of the 41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1317–1320 (2018)

2. Alharbi, A., Briggs, W., Stevenson, M.: retrieving and ranking studies for systematic reviews: University of Sheffield’s Approach to CLEF eHealth 2018 Task 2. In: CEUR Workshop Proceedings: Working Notes of CLEF 2018: Conference and Labs of the Evaluation Forum. vol. 2125. CEUR Workshop Proceedings (2018)

3. Alharbi, A., Stevenson, M.: Ranking abstracts to identify relevant evidence for systematic reviews: the university of sheffield’s approach to clef ehealth 2017 Task 2. In: CEUR Workshop Proceedings: Working Notes of CLEF 2017: Conference and Labs of the Evaluation Forum (2017)

4. Alshami, A., Elsayed, M., Ali, E., Eltoukhy, A.E., Zayed, T.: Harnessing the power of chatgpt for automating systematic review process: methodology, case study, limitations, and future directions. Systems 11(7), 351 (2023)

5. Anagnostou, A., Lagopoulos, A., Tsoumakas, G., Vlahavas, I.P.: Combining inter-review learning-to-rank and intra-review incremental training for title and abstract screening in systematic reviews. In: CEUR Workshop Proceedings: Working Notes of CLEF 2017: Conference and Labs of the Evaluation Forum (2017)

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