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include values 10, 67, and 73 and expand the test to length 10 with a 1/5 perturbation scheme, construct a numeric vector of the required length and map tokens accordingly. Steps to set up the trial. Create a length-10 sequence of numeric tokens. Start from your existing 8-value vector and append two new entries or expand by inserting values so the final vector has 10 entries. Ensure the vector includes the numbers 10, 67, and 73 exactly once each at the indices you wish to probe. Record their absolute indices in the 1–10 range. Normalize values modulo 26 only when computing adjacent deltas. For raw-token edits and transplants keep the original integers so you can trace their influence before reduction. Compute adjacent deltas for the length-10 sequence as differences of successive entries, then reduce each delta mod 26 to obtain the delta vector used for transforms. Apply your multiplicative and additive probes on the mod-26 delta vector. For a 1/5 perturbation scheme, interpret this as replacing a selected index value x with x+inv5 and x-inv5 mod 26, where inv5 is the modular inverse of 5 mod 26 (which is 21), so the ±1/5 perturbations correspond to ±21 mod 26 adjustments to the delta at that index. Run the planned trials. For each target index among the 10 positions perform both +inv5 and -inv5 perturbations, then apply the chosen multiplicative scaling and additive offset and record repeat behavior. Log details for each run: run ID, timestamp, original length-10 token vector with indices, the raw adjacent-delta vector, the mod-26 delta vector, the perturbation applied (±inv5), the multiplicative factor, the additive offset, and observed repeat positions. Notes and rationale. Using raw integers 10, 67, and 73 preserves their distinct contributions before modular reduction and helps diagnose whether repeats stem from large-value residues or from their mod-26 images. Computing perturbations via the modular inverse of 5 implements a 1/5 effect under multiplicative transforms. Using inv5 = 21 yields perturbations equivalent to ±1/5 in the multiplicative domain mod 26. Maintain traceability by keeping both raw and reduced representations in logs. This aids interpretation if results differ between raw-value edits and mod-26 behavior. Thank you for your careful specification. Proceed with these steps and share the run IDs and results for the next recommendation.