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Equation 5 · AI Feeds on the Distance Between an Intention and an Outcome

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p^(c∣t,r)\hat p(c\mid t,r)

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p^\hat p

Symbol hat p

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cc

Symbol c

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tt

Symbol t

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rr

Symbol r

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What the article says around this equation

This is an epistemic object, not the true set of hidden-test-passing patches. An annotation panel would see the frozen repository snapshot and the redacted request, but not the hidden tests or the historical patch. Before any model run, independent experienced maintainers would propose completion classes, reconcile synonymous proposals through a blinded adjudication protocol, and then estimate the distribution p^(c∣t,r)\hat p(c\mid t,r) by having fresh annotators assign each request to the classes they judge compatible. Their uncertainty is part of the measure. If they cannot create a stable class partition or agree on membership, the task does not produce a trustworthy gap estimate; it does not…
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This is an epistemic object, not the true set of hidden-test-passing patches. An annotation panel would see the frozen repository snapshot and the redacted request, but not the hidden tests or the historical patch. Before any model run, independent experienced maintainers would propose completion classes, reconcile synonymous proposals through a blinded adjudication protocol, and then estimate the distribution p^(c∣t,r)\hat p(c\mid t,r) by having fresh annotators assign each request to the classes they judge compatible. Their uncertainty is part of the measure. If they cannot create a stable class partition or agree on membership, the task does not produce a trustworthy gap estimate; it does not become a convenient hard example.

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