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CAI\mathrm{CAI}

Why this formula appears here

State in advance what each outcome would mean, so the test can be graded rather than argued with after the fact. To make the arithmetic concrete — using invented placeholder numbers only, to illustrate what the ratio means, not anything measured — suppose CfC’s Urban Patio baseline stayed at its published 67.5% while its measured CAI\mathrm{CAI} under the recolor intervention came back at 61%. That would give RRR(CfC)\mathrm{RRR}(\mathrm{CfC}) ≈\approx 0.90 : high, and hard to explain without the network actually tracking the target’s identity rather than its color. Suppose instead the same baseline of 67.5% paired with a measured CAI\mathrm{CAI} of 9%, most of those trials converging on the red decoy…

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Published contexts (2)

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CAI\mathrm{CAI}

Equation 11 · AI Research

Every Test Changed the Scene and Kept the Chair Red

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

State in advance what each outcome would mean, so the test can be graded rather than argued with after the fact. To make the arithmetic concrete — using invented placeholder numbers only, to illustrate what the ratio means, not anything measured — suppose CfC’s Urban Patio baseline stayed at its published 67.5% while its measured CAI\mathrm{CAI} under the recolor intervention came back at 61%. That would give RRR(CfC)\mathrm{RRR}(\mathrm{CfC}) ≈\approx 0.90 : high, and hard to explain without the network actually tracking the target’s identity rather than its color. Suppose instead the same baseline of 67.5% paired with a measured CAI\mathrm{CAI} of 9%, most of those trials converging on the red decoy…

Equation guide → · Article →
CAI\mathrm{CAI}

Equation 13 · AI Research

Every Test Changed the Scene and Kept the Chair Red

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

State in advance what each outcome would mean, so the test can be graded rather than argued with after the fact. To make the arithmetic concrete — using invented placeholder numbers only, to illustrate what the ratio means, not anything measured — suppose CfC’s Urban Patio baseline stayed at its published 67.5% while its measured CAI\mathrm{CAI} under the recolor intervention came back at 61%. That would give RRR(CfC)\mathrm{RRR}(\mathrm{CfC}) ≈\approx 0.90 : high, and hard to explain without the network actually tracking the target’s identity rather than its color. Suppose instead the same baseline of 67.5% paired with a measured CAI\mathrm{CAI} of 9%, most of those trials converging on the red decoy…

Equation guide → · Article →