What does this equation mean?

Say check A independently has recall $r_A$ against a real defect — the fraction of the time it would catch that class of problem if it ran — and check B has recall $r_B$ . If the two checks fail for unrelated reasons, the chance a defect slips past both is the product of the chances it slips past each: $P_{miss} = (1-r_A)(1-r_B)$. 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.