GAIDeT – Making AI Use in Research Visible, Comparable and Reusable
This poster was presented at the 30th Annual International Conference on Science and Technology Indicators (STI-ENID 2026), held in Antwerp, Belgium, 9–11 September 2026. The poster presents GAIDeT as an approach for moving from narrative generative AI-use disclosures towards structured, machine-readable research information. It illustrates how GAIDeT-based descriptions could become reusable metadata within scholarly infrastructures and provide contextual information for scientometrics and research evaluation. This poster accompanies the conference paper From citation metrics to LLM judgement: a GAIDeT-based framework for structured AI disclosure.
Authors
- Сергій Андрійович Назаровець (ORCID: https://orcid.org/0000-0002-5067-4498)
- Natalia Tsybuliak (ORCID: https://orcid.org/0000-0003-2474-8614)
- Yana Suchikova (ORCID: https://orcid.org/0000-0003-4537-966X)
- Jaime A. Teixeira da Silva (ORCID: https://orcid.org/0000-0003-3299-2772)
Institutions
- Borys Grinchenko Kyiv Metropolitan University (UA)
- Berdyansk State Pedagogical University (UA)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-09
- DOI
- https://doi.org/10.5281/zenodo.22670652
- Primary Topic
- Research Data Management Practices
- Type
- article
- Field-Weighted Citation Impact
- 0.00