ROUND 4: The 21x storage cost for multi-scale was flagged as possibly unjustified. Can you reduce it? The narrow regime (96.9%-99.8%) where multi-scale matters seems tiny. BUT: Debate D's semantic embeddings are NOISY during cold-start. Does multi-scale help there? Derive: what is the pattern completion success rate on a semantic embedding that has only seen 100 occurrences (vs the 650 needed for convergence)?
