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@@ -62,6 +62,9 @@ the largest size. SDIL reduces the excess final-error growth slope by 96.2% and stable-failure growth by 89.5% relative to static calibration. At 2,048 edges it uses 23.3% fewer local updates to the censored target but 52.8% more local scalar reads because each update includes a neutral measurement. +Increasing static calibration from 16 to 256 instruction-off observations per +edge does not repair the largest network: final error changes from 27.19% to +30.31%, and the paired task-bootstrap interval favors the smaller budget. Start with [`THREE_PART_EVIDENCE.md`](THREE_PART_EVIDENCE.md) for the evidence map and [`CLLN_SCALING.md`](CLLN_SCALING.md) for the frozen scaling protocol. |