These findings suggest a persistent generalization bias in many LLMs, i.e. a tendency to extrapolate scientific results beyond the claims found in the material that the models summarize, underscoring the need for stronger safeguards in AI-driven science summarization to reduce the risk of widespread misunderstandings of scientific research.

From the conclusion. That means that the LLMs give information that is not supported by the actual article.