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Diffstat (limited to 'results.md')
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@@ -126,13 +126,22 @@ Middle-layer ratio across seeds: 1.47 +/- 0.09 (SD), bootstrap 95% CI [1.37, 1.53]. The frequency anti-correlation holds, but the lens also carries genuine conditional-predictability signal. -CAVEAT (from adversarial review): '#' was inserted at uniform random character -positions, which slices through the middle of a word 58% of the time (letter -on both sides: th#e, ki#ng); '@' always sits at a clean word boundary after -"the ". Predictability is therefore not perfectly isolated from n-gram -corruption. A clean-boundary control (noise token after random word -boundaries, 0% word-slicing) is running; the numbers above should be read with -that caveat until it lands. +CAVEAT + CONTROL (resolved): '#' was originally inserted at uniform random +character positions, which slices through the middle of a word 58% of the time +(letter on both sides: th#e, ki#ng); '@' always sits at a clean word boundary +after "the ". A clean-boundary control (noise token after random word +boundaries, 0% word-slicing, same frequency) was run with three fresh seeds: + +``` + placement of '#' middle-layer ratio @/# bootstrap 95% CI + random (58% slicing) 1.471 +/- 0.090 [1.368, 1.529] + clean boundary (0%) 1.311 +/- 0.079 [1.258, 1.402] +``` + +Reading: the corruption confound was real (inflated the ratio by ~12%) but not +the whole story — the structure signal survives at clean boundaries, CI +entirely above 1 in every seed. Original run: outputs/synth_pair/seed{s}/; +control run: outputs/synth_pair_clean/seed{s}/. ## 3. Loss-reweighting causal test (`src/loss_reweight.py`) |
