Conceptual Model and Open Tool for the Standardized Disclosure of Generative AI Use in Scientific Production
DOI:
https://doi.org/10.62059/LatArXiv.preprints.634Keywords:
Generative artificial intelligence, Large language models, Scientific publishing ethics, Transparency, Scholarly authorship, Data governance, Open science, Academic integrityAbstract
The accelerated adoption of generative artificial intelligence (GenAI) in academic writing and research is outpacing the development of clear, harmonized editorial policies. Current responses oscillate between outright bans and unreported use. Although organizations such as COPE and the ICMJE, as well as major publishers, have issued general guidance, there is still no standardized mechanism to operationalize these principles in a way that is granular, interoperable, and verifiable.
This whitepaper proposes a conceptual model for disclosing GenAI use in scholarly production, structured around: (1) a taxonomy of uses that distinguishes between assistance, co-creation, and substantive transformation; (2) an operational human review and oversight scale with six levels (0–5); and (3) a dual output (human-readable structured text and machine-readable JSON) coupled with cryptographic verification.
As a reference implementation, we present usoeticoia.org, an open tool that operationalizes this model through a four-step assistant. The platform generates both outputs and a verification hash, and it is designed to support integration into editorial management systems and open scholarly publishing workflows.
During its first week of operation (December 2025), the platform generated 8 declarations and collected 16 public signatories from 16 countries and institutions. These figures should be interpreted as preliminary signals; they do not allow inference about population-level adoption rates nor causal impact.
References
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[8] Sampaio, R. "La paradoja de la transparencia en el uso de IA generativa." SciELO en Perspectiva, 2025. / Sampaio, R., Sabbatini, M. & Limongi, J. "Diretrizes para uso ético de IAG em produção acadêmica." 2024.
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[11] Miao, F. & Holmes, W. "Guidance for generative AI in education and research." UNESCO, 2023. https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research
[12] TEQSA (Tertiary Education Quality and Standards Agency, Australia). "Comunicados y guías sobre uso de IA en investigación y educación superior." 2024-2025.
[13] Lopes, P. et al. "Análisis de directrices sobre IA generativa en asociaciones científicas brasileñas." 2024.
[14] Gomes, S. & Mendes, L. "Panorama de directrices sobre IA en revistas indexadas por CAPES." 2025.
[15] usoeticoia.org. "Aviso de Privacidad Integral." Diciembre 2025. https://declarador.usoeticoia.org/es/privacidad/
[16] usoeticoia.org. "Glosario de términos." Diciembre 2025. https://declarador.usoeticoia.org/es/glosario/
[17] usoeticoia.org. "Firmantes del compromiso ético y verificación de declaraciones." https://declarador.usoeticoia.org/es/firmantes/
[18] Association of College and Research Libraries (ACRL). "AID Framework for AI Disclosure." 2024.
[19] Resnik, D. & Hosseini, M. "Criterios para determinar obligatoriedad de declaración de uso de IA." 2025.
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Data Availability Statement
Los datos de investigación y el código fuente están disponibles en el repositorio público: https://github.com/escire/usoeticoia-declarador bajo licencia de código abierto. El esquema JSON de referencia se encuentra disponible en https://github.com/escire/usoeticoia.org-declarador/blob/v1.1.0/core/schema.json
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Copyright (c) 2026 German Díaz Hernández (Autor/a)
This work is licensed under a Creative Commons Attribution 4.0 International License.
This preprint contains the reported license and associated copyright. Once published in an associated journal or other publisher, the published version assumes the publisher's terms and conditions.
