# Predictions

`kaal:entity:predictions`

**Status.** derived

This node is assembled mechanically from the 2 claims that carry the concept tag `predictions`. 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

2 claims across 1 works, 2026 to 2026.

**2026**

- [6192998-033](https://wulfkaal.github.io/claims/6192998-033) [predictive/speculative] -- In mature knowledge domains using citation weighted reputation, foundational contributors will accumulate ten to one hundred times more reputation than equivalent quality incremental contributors, and citation graphs will exhibit power law degree distributions.
  > - Foundational contributors accumulate 10-100× more reputation than equivalent-quality incremental contributors - Citation graphs exhibit power-law degree distribution (Barabási-Albert model)
  Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998
- [6192998-036](https://wulfkaal.github.io/claims/6192998-036) [predictive/speculative] -- Domains using multi agent competition will exhibit fifteen to thirty percent higher quality scores than single agent selection, controlling for agent capability.
  > Expertise domains using multi-agent competition will exhibit 15-30% higher quality scores compared to single-agent selection, controlling for agent capability.
  Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998

## 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/predictions.md | sha256sum

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