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揭示科学文献领域中的拉森效应:在人工智能驱动的洪流中驾驭质量。

Unveiling the Larsen effect in the scientific literature domain: Navigating quality amidst the artificial intelligence-driven deluge.

机构信息

Department of Social Sciences, K-Synth Academic Spin-Off, University of Naples Federico II, Naples, Italy.

出版信息

J Oral Pathol Med. 2024 Jul;53(6):331-333. doi: 10.1111/jop.13569. Epub 2024 Jun 25.

Abstract

The challenges faced by the massive increase in scientific publications draw parallels to the Larsen effect, where an amplified sound loop leads to escalating noise. This phenomenon has resulted in information overload, making it difficult for researchers to stay updated and identify significant findings. To address this, knowledge synthesis techniques are recommended. These methods help synthesize and visualize large bodies of literature, aiding researchers in navigating the expanding information landscape. Furthermore, artificial intelligence (AI) and natural language processing tools, such as text summarization, offer innovative solutions for managing information overload. However, the overuse of AI in producing scientific literature raises concerns about the quality and integrity of research. This manuscript highlights the need for balanced use of AI tools and collaborative efforts to maintain high-quality scientific output while leveraging the benefits of extensive research.

摘要

科学出版物的大量增长所面临的挑战与拉森效应(Larsen effect)类似,在拉森效应中,放大的声音循环会导致噪音不断升级。这种现象导致了信息过载,使得研究人员难以跟上最新进展并发现重要发现。为了解决这个问题,推荐使用知识综合技术。这些方法有助于综合和可视化大量文献,帮助研究人员在不断扩展的信息环境中进行导航。此外,人工智能(AI)和自然语言处理工具,如文本摘要,为管理信息过载提供了创新的解决方案。然而,在生成科学文献中过度使用人工智能引起了人们对研究质量和完整性的担忧。本文强调了需要平衡使用 AI 工具和协作努力,以在利用广泛研究的好处的同时保持高质量的科学产出。

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