Fix one admitted assisted campaign with final score \(Z\in [0,1]\). Suppose an autonomous campaign is admitted under the same external resource caps and evaluation convention, with simulation, development and recipient learning fully charged. If its joint law of transcript, retained artifact and fresh evaluation agrees with that of the assisted campaign, then its expected acquisition score is identical.

More generally, if these laws have total variation distance at most \(\varepsilon \), where \(\operatorname {TV}(P,Q)=\sup _A|P(A)-Q(A)|\), then \(|\mathbb E_PZ-\mathbb E_QZ|\leq \varepsilon \). Indeed, \(\mathbb E_PZ=\int _0^1P(Z>t)\,dt\), and the probability difference in each integrand is at most \(\varepsilon \). Thus the autonomous score is at least \(Q_{\rm acq}^{\rm assisted}-\varepsilon \).

Approximate agreement of output laws does not establish an almost-sure resource cap: admission of the autonomous implementation is a separate premise. Nor does computability establish affordable reconstruction of the contributor's development and observations. This is the economic version of the reconstruction boundary; a claimed separation must exclude such an affordable implementation by an actual lower bound.