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Equation 6 · Part 2 · Every Test Changed the Scene and Kept the Chair Red

Symbol N

CAI(π)=1N∑i=1N1[trial i converges on the recolored true target, not the red decoy, within the paper’s own 2-meter success radius].\mathrm{CAI}(\pi) = \frac{1}{N}\sum_{i=1}^{N} \mathbb{1}\left[\text{trial } i \text{ converges on the recolored true target, not the red decoy, within the paper's own 2-meter success radius}\right] .
NN

What this part means

N occurs below the fraction bar. The quantity above the bar is divided by this expression; zero is excluded as a denominator.

Its job in the formula

N occurs below the fraction bar. The quantity above the bar is divided by this expression; zero is excluded as a denominator.

The passage around this formula

A countermodel earns its keep only once it points at a specific, buildable measurement nobody has taken. Define, for any policy π\pi , a Causal-Alignment Index under a cue-decorrelation intervention that repaints the true target a color other than red while placing an unmodified red decoy elsewhere in the same frame region class the paper’s own Urban Patio protocol already uses: CAI(π)=1N∑i=1N1[trial i converges on the recolored true target, not the red decoy, within the paper’s own 2-meter success radius]\mathrm{CAI}(\pi) = \frac{1}{N}\sum_{i=1}^{N} \mathbb{1}\left[\text{trial } i \text{ converges on the recolored true target, not the red decoy, within the paper's own 2-meter success radius}\right] . Pair it with a Recolor Robustness Ratio , comparing that score against the architecture’s own already-published performance on the paper’s hardest matched-appearance site:

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