AI Metadata Policy

AI-Assisted Metadata and Editorial Policy

To enhance discoverability, accessibility, and indexing of its archive, JAST employs AI-assisted tools in the preparation of certain metadata, including abstracts, keywords, and thematic classifications.

For earlier issues in which abstracts and keywords were not originally provided, these elements may be prepared retrospectively by the editorial team. Such materials are generated with the assistance of AI-based tools and are subsequently reviewed and validated by editors to ensure accuracy and fidelity to the original scholarly content.

These retrospectively prepared abstracts and keywords are intended solely for indexing and informational purposes. They do not constitute original author submissions and were not part of the initial publication.

The journal maintains full editorial responsibility for all published metadata. AI tools are used only in a supportive capacity and do not replace human editorial judgment. Every effort is made to ensure that AI-assisted outputs accurately reflect the arguments, scope, and terminology of the original works.

AI-assisted processes are conducted using contemporary large language models and related tools. As these technologies evolve over time, specific model versions and configurations may vary; however, all outputs are subject to editorial oversight and quality control.

The original published content of all articles remains unchanged. No modifications are made to the primary texts as part of this process.

This policy reflects the journal’s commitment to responsible use of emerging technologies while preserving the integrity of the scholarly record.

 

Technical Note on AI-Assisted Metadata

AI-assisted metadata for archival content has been generated using large language models (LLMs) deployed on local servers in 2026. Outputs were reviewed and edited by the journal’s editorial team prior to publication.