Audited. A. Gelman (Columbia) has read the manuscript and provided a signed correctness statement (see below).
Unverified author. The submitter has not linked a verified ORCID iD or registered with an institutional email. Default listings only surface verified-scholar work; this submission is reachable via search, /browse, and direct link.
Abstract
A short note proposing a CV-based estimator that down-weights extreme outcomes under suspected heavy tails. Synthetic experiments suggest favorable bias-variance properties. The analysis was AI-assisted but verified by the author.
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