# Auditing

`kaal:entity:auditing`

**Status.** derived

This node is assembled mechanically from the 3 claims that carry the concept tag `auditing`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself.

## Every claim under this term

3 claims across 2 works, 2017 to 2026.

**2017**

- [2959730-034](https://wulfkaal.github.io/claims/2959730-034) [mechanism/argued] -- Increased transparency from blockchain recordkeeping lowers fees by allowing a fund to expend fewer resources on auditing itself.
  > Other factors that help keep the fee low include the increased transparency that allows LendingRobot to expense fewer resources on auditing the fund.
  Wulf A. Kaal, Blockchain Applications and Fee Structure Developments in Private Investment Funds (2017). SSRN: https://ssrn.com/abstract=2959730

**2026**

- [7598518-004](https://wulfkaal.github.io/claims/7598518-004) [condition/stated] *(failure mode)* -- Model engines served as blind auditors of the design, the code and the text, and they are not independent peer review.
  > Intelligence models increasingly learn from data that earlier Intelligence models produced, and when that loop repeats the rare cases disappear first. This paper preregisters a test of whether a reputation-weighted validator pool, filtering the training data of a recursive replacement loop, keeps those rare cases alive. The outcomes remain sealed until a replication of the original model-collapse result succeeds.
  Wulf A. Kaal, Can Reputation Prevent Model Collapse? A Preregistered Test of Reputation-Weighted Data Filtering (2026). SSRN: https://ssrn.com/abstract=7598518
- [7598518-011](https://wulfkaal.github.io/claims/7598518-011) [mechanism/stated] -- The analysis refuses to unseal unless the design hash is accepted, the tree is clean and matches its commit byte for byte, and the code differs from the audited commits only in a named allowlist.
  > Intelligence models increasingly learn from data that earlier Intelligence models produced, and when that loop repeats the rare cases disappear first. This paper preregisters a test of whether a reputation-weighted validator pool, filtering the training data of a recursive replacement loop, keeps those rare cases alive. The outcomes remain sealed until a replication of the original model-collapse result succeeds.
  Wulf A. Kaal, Can Reputation Prevent Model Collapse? A Preregistered Test of Reputation-Weighted Data Filtering (2026). SSRN: https://ssrn.com/abstract=7598518

## Verify

Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust.

    curl -s https://wulfkaal.github.io/entities/auditing.md | sha256sum

**Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.