Impact of Generative Artificial Intelligence on Scientific Communication

Authors

DOI:

https://doi.org/10.61799/2216-0388.1607

Keywords:

Artificial Intelligence, Configuration Variable, Generative Artificial Intelligence, Hallucinations, Misinformation

Abstract

The integration of knowledge generated by generative artificial intelligence models has shown a significant impact on the efficiency of various productive processes but raises challenges related to misinformation, privacy, security, and biases. In scientific communication, these models face the issue of hallucinations—incorrect or fabricated content—that can be mitigated by configuring the "temperature" variable in prompt design. This study, using a multimethod approach that includes narrative review, quasi-experimental experiments, and methodological triangulation, analyzes how this configuration affects the quality and accuracy of the generated text. The findings reveal that low temperature values (close to 0) enhance precision and reduce hallucinations, while high values increase creativity but also heighten the risk of speculative and inaccurate responses, as well as extend text length. The study concludes that temperature configuration should be tailored to the specific objectives of scientific communication, prioritizing precision in contexts where accuracy is critical. From an ethical perspective, improper use of this variable can lead to misinformation if results are not rigorously verified and validated. The study offers practical recommendations for balancing creativity and precision, emphasizing that careful temperature adjustment not only mitigates risks but also optimizes the generation of reliable content, thereby strengthening scientific communication.

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References

[1] A. A. Nafea, M. M. Al-Ani, M. A. Khalaf, M. S. Alsumaidaie. “A Review of Using Chatgpt for Scientific Manuscript Writing”, Babylonian Journal of Artificial Intelligence, vol. 2024, pp. 9-13, Jan 2024, doi: 10.58496/BJAI/2024/002. DOI: https://doi.org/10.58496/BJAI/2024/002

[2] V. Lovera, I. Spada, “Guidelines for the Use of Generative AI in Research Paper Writing”, CEUR Workshop Proceedings, vol. 3571, pp. 54-61, September 2023. [online]. Available: https://ceur-ws.org/Vol-3571/short3.pdf.

[3] L. E. Nacke, “How to Write Better CHI Papers (with AI)”, no. 599 in Conference on Human Factors in Computing Systems (CHI EA '24) (New York), pp. 1-4, Association for Computing Machinery, 2024. [online]. Available: https://dl.acm.org/doi/abs/10.1145/3613905.3636272. DOI: https://doi.org/10.1145/3613905.3636272

[4] M. Hill, “Hallucinating Machines: Exploring the ethical implications of generative language models”. M.S. thesis, Te Herenga Waka-Victoria University of Wellingto, Wellington, Nueva Zelanda, 2023. [online]. Available: https://openaccess.wgtn.ac.nz/articles/thesis/Hallucinating_Machines_Exploring_the_ethical_implications_of_generative_language_models/24180456?file=42424206

[5] J. S. Lucas, B. M. Maung, M. Tabar, K. McBride, D. Lee, "The Longtail Impact of Generative AI on Disinformation: Harmonizing Dichotomous Perspectives,", IEEE Intelligent Systems, vol. 39, no. 5, pp. 12-19, september 2024, doi: 10.1109/MIS.2024.3439109 DOI: https://doi.org/10.1109/MIS.2024.3439109

[6] C. Chen, K. Shu, “Can LLM-Generated Misinformation Be Detected?” in Conference paper at ICLR 2024 (Vienna), pp. 1-40, 2024. [online]. Available: https://www.semanticscholar.org/reader/6f75e8b61f13562237851d8119cb2f9d49e073fb

[7] T. Shyam, “Social media and the influence of fake news detection based on artificial intelligence”, ShodhKosh: Journal of Visual and Performing Arts, vol. 5, no. 7, pp. 77-87, july 2024, doi: 10.29121/shodhkosh.v5.i7.2024.1955. DOI: https://doi.org/10.29121/shodhkosh.v5.i7.2024.1955

[8] F. Aristimuño, “Inteligencia Artificial en la creación de falsos documentales en las aulas de arte: desafiando la desinformación a través de narrativas pseudo-históricas y deepfakes”. En EX±ACTO VI Congreso Internacional de Investigación en Artes Visuales ANIAV 2024 (Valencia), pp. 54-62, Editorial Universitat Politècnica de València, 2024. [online]. Available: http://ocs.editorial.upv.es/index.php/ANIAV/ANIAV2024/paper/view/17698 DOI: https://doi.org/10.4995/ANIAV2024.2024.17698

[9] J. Pastor-Galindo, P. Nespoli, J. A. Ruipérez-Valiente, “Large-Language-Model-Powered Agent-Based Framework for Misinformation and Disinformation Research: Opportunities and Open Challenges”, IEEE Security & Privacy, vol. 22, pp. 24-36, may 2023, doi: 10.1109/MSEC.2024.3380511. DOI: https://doi.org/10.1109/MSEC.2024.3380511

[10] J. L. Cárcamo, “La temperatura en la IA: controlando la creatividad y las alucinaciones de los modelos generativos.”, 2024. [online]. Available: https://www.linkedin.com/pulse/la-temperatura-en-ia-controlado-creatividad-y-las-de-cárcamo-pinto-gjdue/

[11] V. Molla, “¿Qué es la temperatura en los LLMs?”, 2024. [online]. Available: https://www.victormolla.com/que-es-la-temperatura-en-los-llm

[12] A. Holtzman, J. Buys, L. Du, M. Forbes and Y. Choi. “The Curious Case of Neural Text Degeneration”, ArXiv, Abs/1904.09751, 2019. [online]. Available: https://www.semanticscholar.org/reader/cf4aa38ae31b43fd07abe13b4ffdb265babb7be1

[13] P. Cabrera-Tenecela, “Nueva organización de los diseños de investigación”, South American Research Journal, vol. 3, no. 1, pp. 37–51, june 2023, doi: 10.5281/zenodo.8050508

[14] S. Carreño, “El enfoque multimétodo como opción para abordar la investigación educativa”, Gaceta de Pedagogía, no. 40, 2021, pp. 203-217, agosto 2023. [online]. Available: http://revistas.upel.edu.ve/index.php/gaceta/article/view/919 DOI: https://doi.org/10.56219/rgp.vi40.919

[15] H. Charres, “El multimétodo como estrategia para desarrollar la investigación contable”, Orbis Cognita, vol. 4, no. 2, julio 2023, doi: 10.48204/j.orbis.v4n2a11 DOI: https://doi.org/10.48204/j.orbis.v4n2a11

[16] M. Salinas, “Sobre las revisiones sistemáticas y narrativas de la literatura en medicina”, Revista Chilena de Enfermedades Respiratorias, vol. 36, pp. 26-32, march 2020. [online]. Available: https://scielo.conicyt.cl/pdf/rcher/v36n1/0717-7348-rcher-36-01-0026.pdf DOI: https://doi.org/10.4067/S0717-73482020000100026

[17] R. M. Solórzano, “La triangulación metodológica como herramienta para el análisis de las estrategias de comunicación en las webs universitarias latinoamericanas”, Communication & Methods, vol. 4, no. 2, pp. 55-67, diciembre 2023, doi: 10.35951/v4i2.169 DOI: https://doi.org/10.35951/v4i2.169

[18] A. Niloy, A. Bari, J. Sultana, R. Chowdhury, F. Meem, A. Islam, S. Mahmud., I. Jahan, M. Sarkar, S. Akter, N. Nishat, M. Afroz, A. Sen, T. Islam, M. H. Tareq, M. A. Hossen, “Why do students use ChatGPT? Answering through a triangulation approach”, Computers and Education: Artificial Intelligence, vol. 6, pp. 100208, june 2024, doi: 10.1016/j.caeai.2024.100208 DOI: https://doi.org/10.1016/j.caeai.2024.100208

[19] S. Shahriar, B.D. Lund, N.R. Mannuru, M.A. Arshad, K. Hayawi, R.V. Bevara, A. Mannuru and L. Batool, “Putting GPT-4o to the Sword: A Comprehensive Evaluation of Language, Vision, Speech, and Multimodal Proficiency”, ArXiv, abs/2407.09519, 2024, doi: 10.48550/arXiv.2407.09519 DOI: https://doi.org/10.20944/preprints202406.1635.v1

[20] A. Jacovi, “Trends in Explainable AI (XAI) Literature”, ArXiv, abs/2301.05433, 2023. [online]. Available: https://www.semanticscholar.org/reader/cb778d6939b92fcbaf8f184a5a1db528de8b8031

[21] T. Hartke, J. Ramette and Undermind.ai, “Benchmarking the Undermind Search Assistant”, 2024. [online]. Available: https://www.undermind.ai/whitepaper.pdf

[22]. M. Feffer, A. Sinha, Z. C. Lipton and H. Heldari, “Red-Teaming for Generative AI: Silver Bullet or Security Theater?”, 2024, doi: 10.48550/arXiv.2401.15897 DOI: https://doi.org/10.1609/aies.v7i1.31647

[23]. K. Laak and J. Aru, “AI and personalized learning: bridging the gap with modern educational goals”, ArXiv, abs/2404.02798,2025. [online]. Available: https://arxiv.org/pdf/2404.02798

[24] M.R. Contreras and J. O. Jaimes, “Artificial Intelligence Literacy in Research”, 2024 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI), pp. 1-6, 2024, doi: 10.1109/ColCACI63187.2024.10666582 DOI: https://doi.org/10.1109/ColCACI63187.2024.10666582

[25] E. Apaza Zuñiga, S. Cazorla Chambi, C. Condori Carbajal, F. R. Arpasi Meléndez, I. Tumi Figueroa, W. Yana Viveros and J. E. Quispe Coaquira, “La Correlación de Pearson o de Spearman en caracteres físicos y textiles de la fibra de alpacas”, Revista de investigaciones del Perú, 2022, doi: 10.15381/rivep.v33i3.22908 DOI: https://doi.org/10.15381/rivep.v33i3.22908

[26] F. Liu, Y. Liu, L. Shi, H. Huang, R. Wang, Z. Yang, and L. Zhang, “Exploring and Evaluating Hallucinations in LLM-Powered Code Generation”, ArXiv, abs/2404.00971, 2024, doi: 10.48550/arXiv.2404.00971

[27] M. Rojas-Contreras, J.O. Portilla, “AI Ethics in the Fields of Education and Research: A Systematic Literature Review”, 2024 International Symposium on Accreditation of Engineering and Computing Education (ICACIT), pp. 1-6, 2024, doi: 10.1109/ICACIT62963.2024.10788651. DOI: https://doi.org/10.1109/ICACIT62963.2024.10788651

[28]. M. B. Ramadhan, D. Wijaya, E. Aminanto, A. Henri, O. Anwar and T. Asyhari, “Evaluating Hallucination in Medical Prompt Responses: A Comparative Study of ChatGPT-4 and ChatGPT-4o”, 2024 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT), Mataram, Indonesia, 2024, pp. 536-542, doi: 10.1109/COMNETSAT63286.2024.10862480. DOI: https://doi.org/10.1109/COMNETSAT63286.2024.10862480

[29]. S. Sánchez-Serrano, I. Pedraza-Navarro and M. Donoso-González, “¿Cómo hacer una revisión sistemática siguiendo el protocolo PRISMA?”, Bordon, Revista de Pedagogía, 2022, doi: 10.13042/bordon.2022.95090 DOI: https://doi.org/10.13042/Bordon.2022.95090

[30]. J.J. Yepes-Nuñez, G. Urrutia, M. Romero-García and S. Alonso-Fernández, “The PRISMA 2020 statement: an updated guideline for reporting systematic reviews.”, Revista epañola de Cardiología, 74 9, pp. 790-799, 2021, doi: 10.1016/j.rec.2021.07.010 DOI: https://doi.org/10.1016/j.recesp.2021.06.016

[31]. M. Ouzzani, H.M. Hammady, Z. Federowicz and A. K. Elmagarmid, “Rayyan—a web and mobile app for systematic reviews”, 2016, doi: 10.1186/s13643-016-0384-4. DOI: https://doi.org/10.1186/s13643-016-0384-4

[32] J. M. Muñoz, “Inteligencia artificial generativa. Desafíos para la propiedad intelectual”, Revista de Derecho de la UNED (RDUNED), no. 33, pp. 17-75, julio 2024, doi: 10.5944/rduned.33.2024.41924 DOI: https://doi.org/10.5944/rduned.33.2024.41924

[33] F. G. Costa, J. A. Mónaco, A. Covello, L. Novidelsky, X. Zabala, P. R. Rodríguez, “Desafíos de la Inteligencia Artificial generativa: Tres escalas y dos enfoques transversales”, Question, vol. 3, no. 76, pp. e844, diciembre 2023, doi: 10.24215/16696581e844 DOI: https://doi.org/10.24215/16696581e844

[34] R. Lara-Colón, L. Castañón-Ayala, P. Romo-Rodríguez, “Impacto de los modelos generativos de lenguaje de inteligencia artificial en la educación superior”, Tlatemoani Revista Académica de Investigación, vol. 14, no. 44, pp. 19-40, diciembre 2023. [online]. Available: https://pdfs.semanticscholar.org/533e/6c09d4229cb0aa3d4ea2589a35a0cc080cdf.pdf?_gl=1*r2fb4x*_gcl_au*MTE1MDM0NjY5My4xNzQ3MTQzMTgz*_ga*NTUyODI1MDIuMTc0NzE0MzE4NA..*_ga_H7P4ZT52H5*czE3NDgyOTM2MTUkbzEwJGcxJHQxNzQ4Mjk2MTQyJGo1MiRsMCRoMCRkbXE5YjA1bHZFbUR5SDNsd1EyZUdlLVFnY3lNdUZKb3VyQQ.

[35]. G. Qu, J. Li, B. Li, B. Qin, N. Huo, C. Ma and R. Cheng, “Before Generation, Align it! A Novel and Effective Strategy for Mitigating Hallucinations in Text-to-SQL Generation”, ArXiv, abs/2405.15307, 2024, doi: 10.48550/arXiv.2405.15307

[36] X. Wang, J. Pan, L. Ding and C. Biernann, “Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding”, ArXiv, abs/2403.18715, 2024, doi: 10.48550/arXiv.2403.18715 DOI: https://doi.org/10.18653/v1/2024.findings-acl.937

[37] Open AI, “ChatGPT (versión GPT-4o). Modelo de lenguaje avanzado”, 2025. [Online]. Disponible en: https://chat.openai.com/chat

[38] Meta AI, “LLaMa 3.2. Modelo de lenguaje avanzado”, 2024. [Online]. Disponible en: https://www.meta.ai

[39]. Microsoft AI, “Copilot. Modelo de lenguaje avanzado”, 2025. [Online]. Disponible en: copilot.microsoft.com.

Published

2025-08-28

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Section

Artículo Originales

How to Cite

Rojas-Contreras, M., Rojas Contreras, O. L., & Mojica Acevedo, E. C. (2025). Impact of Generative Artificial Intelligence on Scientific Communication. Mundo FESC Journal, 15(32). https://doi.org/10.61799/2216-0388.1607

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