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$(1-r_A)$

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which is smaller than either (1- $r_A$ ) or (1- $r_B$ ) alone: real, additive protection. But if the two checks share a failure mode — most obviously, if the “second check” is the same model re-reading its own output inside the same context, primed by the same reasoning that produced the mistake — their misses stop being independent, and the joint miss probability climbs back toward $\max(1-r_A,\ 1-r_B)$ : no better than the stronger of the two checks alone, and often worse in practice, because the second pass inherits the first pass’s blind spot along with its confidence.

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r_A

Symbol r_A

$r_A$ is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

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(1-r_A)

Equation 6 · AI Agents & Systems

How Verification Actually Works in a Claude Code Workflow

This mathematical expression combines the displayed quantities; its precise role follows from the surrounding article text.

which is smaller than either (1- $r_A$ ) or (1- $r_B$ ) alone: real, additive protection. But if the two checks share a failure mode — most obviously, if the “second check” is the same model re-reading its own output inside the same context, primed by the same reasoning that produced the mistake — their misses stop being independent, and the joint miss probability climbs back toward $\max(1-r_A,\ 1-r_B)$ : no better than the stronger of the two checks alone, and often worse in practice, because the second pass inherits the first pass’s blind spot along with its confidence.

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(1−rA)(1-r_A)(1−rA​)