Test whether a candidate real-work signal in `eval/token_ceiling_formula.py` (e.g. `context_ingestion_volume`, `investigative_uncertainty`, or new) deserves a nonzero default weight, via the blind multi-draw rating + correlation methodology this repo's research converged on. Ratings must come from genuinely independent sub-agent dispatches seeing ONLY a forward-looking task spec and the signal definitions — never a context holding the real actuals or this repo's retired write-ups, which would turn "blind rating" into transcribing the answer key. Dispatches 3+ independent draws per held-out task, computes per-signal CV and Pearson correlation (alone, and added to the signal sum — dilution, not weak correlation, is the dominant failure found twice), requiring replication on a SECOND held-out task before proposing a nonzero weight. Use when someone says "test this new signal", "does [signal] deserve a nonzero weight", "re-run the signal validation experiment", or "validate real-work signals against real data".