Unbiased Prevalence Estimation with Multicalibrated LLMs

ArXi:2604.21549v1 Announce Type: new Estimating the prevalence of a category in a population using imperfect measurement devices (diagnostic tests, classifiers, or large language models) is fundamental to science, public health, and online trust and safety. Standard approaches correct for known device error rates but assume these rates remain stable across populations.