Benchmarking readability, reliability, and scientific quality of large language models in communicating organoid science

Abstract

LLMs exhibited substantial variability in communicating organoid-related information, forming distinct performance tiers with direct implications for patient education and translational decision-making. Because readability, scientific quality, and reliability diverged across models, linguistic simplification alone is insufficient to guarantee accurate or dependable interpretation. These findings underscore the need for organoid-adapted AI systems that integrate domain-specific knowledge, convey uncertainty transparently, ensure output reliability, and safeguard safety-critical information.

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