莱姆病争议：对四分之一世纪学术辩论与分歧的AI驱动话语分析
The Lyme Disease Controversy: An AI-Driven Discourse Analysis of a Quarter Century of Academic Debate and Divides
AI总结：
本研究针对25年来慢性莱姆病（CLD）和治疗后莱姆病综合征（PTLDS）的学术争议，采用大型语言模型（LLMs）结合人工验证的混合AI方法分析数千篇摘要，揭示其从感染模型向免疫介导解释的转变，提供可扩展的话语分析方法并强调AI辅助价值。
摘要：
过去25年间，围绕慢性莱姆病（CLD）和治疗后莱姆病综合征（PTLDS）的科学话语已演变为一场复杂且两极分化的辩论，其形成受到研究重点转变、机构影响及竞争性解释模型的影响。本研究首次采用创新的混合AI驱动方法，将大型语言模型（LLMs）与结构化人工验证相结合，对25年间的数千篇学术摘要进行分析，开展了对此话语的大规模系统性审视。通过整合大型语言模型（LLMs）与专家监督，我们开发了一个定量框架，用于追踪有争议医学领域的认知转变，并可应用于其他内容分析领域。我们的分析揭示了莱姆病从基于感染的模型向针对持续性症状的免疫介导解释的渐进转变。本研究为塑造莱姆病研究的结构与认知力量提供了新的实证见解，为话语分析提供了可扩展且可复制的方法，同时强调了AI辅助方法在社会科学和医学研究中的价值。
英文摘要：
The scientific discourse surrounding Chronic Lyme Disease (CLD) and Post-Treatment Lyme Disease Syndrome (PTLDS) has evolved over the past twenty-five years into a complex and polarised debate, shaped by shifting research priorities, institutional influences, and competing explanatory models. This study presents the first large-scale, systematic examination of this discourse using an innovative hybrid AI-driven methodology, combining large language models with structured human validation to analyse thousands of scholarly abstracts spanning 25 years. By integrating Large Language Models (LLMs) with expert oversight, we developed a quantitative framework for tracking epistemic shifts in contested medical fields, with applications to other content analysis domains. Our analysis revealed a progressive transition from infection-based models of Lyme disease to immune-mediated explanations for persistent symptoms. This study offers new empirical insights into the structural and epistemic forces shaping Lyme disease research, providing a scalable and replicable methodology for analysing discourse, while underscoring the value of AI-assisted methodologies in social science and medical research.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
