Differential 2D measurement recovers the sheet as composite minus bare support. Each dot below is one simulated differential pair at one value of the sheet’s share of the composite’s transport; every measurement carries the same per-measurement noise. Where the sheet carries most of the signal (right), the recovered values hug the true line; where it carries a sliver (left), the identical instrument scatters wildly — the exact error law for this model is σ/share·√(1+(1−share)²), which approaches √2·σ/share for small shares. The shaded funnel is the ±1σ prediction of exactly that law.
Model: sheet value recovered as the difference of two independent measurements — composite (conductance 1/share) and bare support (1/share − 1) — each with independent Gaussian relative noise σ. The recovered value’s exact relative SD is then σ/share·√(1+(1−share)²): at full share it reduces to σ, and for small shares it approaches the √2·σ/share limit. This is the equal-variance, independent-error teaching model; real campaigns add support-reproducibility, coating and covariance terms (paired designs on the same membrane can be positively correlated, reducing part of the variance while transfer processing adds its own). Axes normalized; schematic teaching tool, not an instrument.