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$(1-r_B)$

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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_B

Symbol r_B

the recall.

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(1-r_B)

Equation 7 · 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.

Meanings in this article

$r_B$ : the recall.

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(1−rB)(1-r_B)(1−rB​)