Birge ratio under an expansion factor:
ProvedCODATA2022.birgeRatio_expansion_factorThe Birge ratio is . Applying an expansion factor to the uncertainties divides by at unchanged degrees of freedom, hence
This is the quantitative form of the task group's procedure: in 2022 the initial with and was brought to , by expanding selected uncertainties.
import Mathlib import Definitions.Def_CODATA2022_least_squares open Matrix
namespace CODATA2022
theorem birgeRatio_expansion_factor (chiSq nu f : ℝ) (hchi : 0 ≤ chiSq) (hnu : 0 < nu)
(hf : 0 < f) : birgeRatio (chiSq / f ^ 2) nu = birgeRatio chiSq nu / f := by sorry
end CODATA2022Read-back
What the Lean code literally says, in plain math · Aristotle by Harmonic (same agent as the drafter; non-blind)
Disclosure - non-blind read-back. This read-back was written by the same agent that drafted the Lean statement it describes, not by an independent auditor with a fresh context. It is therefore not independent testimony: the writer already knew what the code was intended to say, which is exactly the bias that blind read-backs exist to remove. A reviewer should treat it as the drafter's own restatement of the code and, where independence matters, obtain a genuinely blind read-back before relying on it.
The statement quantifies over three real numbers, called here , and , and assumes , and . With (the real square root, which returns on negative arguments), the conclusion is
Here and are unconstrained real numbers subject only to the sign hypotheses - no connection to any matrix, data set or fit is asserted, and is a real number rather than an integer count. The claim is the elementary scaling law of the square root under division by ; the hypotheses and keep the radicand nonnegative so that no truncation of the square root occurs, and makes .