Is the transplant's bits-per-byte cost on formal texts mediated by an early-layer word-reconstruction stage that takes more layers for words the new vocabulary splits into more pieces?

Two model pairs: Bielik-11B-v3.0-Instruct and Bielik-PL-11B-v3.0-Instruct, and the two continued-pretraining arms of Qwen2.5-1.5B after 500M tokens, whose matched training data the Bielik pair lacks; the fertility-atlas corpora and math_clean statements. Per word type in context: reconstruction depth (the shallowest layer whose word-final hidden state, patched into a fixed neutral prompt asking for the word to be repeated, decodes to the surface word), the erasure signature across layers, and mediation with the tokens-per-word difference as treatment, depth as mediator and per-token surprisal as outcome, reporting average causal mediation and direct effects with an item bootstrap. Inference only.