Large language models are reshaping research practice while quietly eroding researchers epistemic accountability. This commentary introduces PEEL - Protocols for Epistemically Engaged Literacy in AI, a working scaffolding that combines deterministic distant reading via Voyant Tools with LLM interpretation via Claude, grounded in Peircean semiotics and abductive reasoning. Applied to AI-generated condensations of three source texts, PEEL reveals systematic distortions in quantity, term frequency, and epistemic voice that are invisible without non-AI measurement -- and yields three design implications: deterministic instruments must accompany AI tools; fluency is not fidelity; epistemic authority must be designed in, not assumed.

翻译：大型语言模型正在重塑研究实践，同时悄然削弱研究者的认识论责任感。本文介绍PEEL——面向AI的认识论参与式素养协议，这是一个工作支架，结合了通过Voyant工具实现的确定性远距离阅读与通过Claude实现的大语言模型解读，并植根于皮尔士符号学与溯因推理。应用于三个源文本的AI生成浓缩文本时，PEEL揭示了数量、词频和认识论声音上的系统性扭曲，这些扭曲若无非AI测量则难以察觉——并得出三项设计启示：确定性工具必须伴随AI工具；流畅性不等于保真度；认识论权威必须内嵌于设计之中，而非默认存在。