# kaal:position:2026-08-08-358

**Affirmed position.** Pizzi, Cepellotti, Sabatini, Marzari, and Kozinsky provide an independent implementation precedent for separating evidentiary completeness from public disclosure. AiiDA records calculations and data as nodes joined by directional, labeled links that preserve the causal chain from input data through intermediate calculations to final results. The system stores queryable node attributes and permits users to inspect the history of a computational result. Its sharing design creates a separate boundary. Each user or group may operate a local instance in which data and calculations remain private. A user may then export only a portion of the database to another instance while retaining the remaining private portion.

The relationship is a qualification. The distinction matters. AiiDA shows that detailed causal provenance and selective disclosure can coexist in one implemented system. It does not record a population of autonomous agents or establish Kaal's generation, lineage, fitness, survival, parentage, reputation, and adjudication fields. The paper also does not validate Kaal's execution record or disclose his private apparatus. This use of AiiDA is limited to its privacy and partial-export mechanism. The previously published AiiDA comparison addressed the distinct proposition that a directed graph can preserve an inspectable computational history. Evidentiary integrity does not require universal access to the system that produces the evidence.

**Status.** affirmed  **Published.** 2026-08-08

**Holds when.**

- The response is limited to the exact public primary-paper proposition and the one mapped Kaal claim.
- External evidence level: complete public 30-page arXiv v2 manuscript of a peer-reviewed journal article with exact PDF SHA-256, page-bound passages, arXiv identity, and Crossref identity.
- Mapping review tier: independent substantive scholarly-growth qualification.
- The source records computational data and calculations, not a population of autonomous agents.
- It does not establish Kaal's generation, lineage, fitness, survival, parentage, reputation, or adjudication fields.
- It does not validate Kaal's execution record or inspect his private apparatus.
- The same source's previously published position addressed inspectable graph history, while this position is limited to local privacy and partial export.

**Current debate.** AiiDA: automated interactive infrastructure and database for computational science: https://doi.org/10.1016/j.commatsci.2015.09.013

**Extends.** kaal:claim:7261481-023: https://wulfkaal.github.io/claims/7261481-023

**Scholarly basis.** Wulf A. Kaal, Computative Economics: A Framework for Economic Analysis under Computational Abundance (2026). SSRN: https://ssrn.com/abstract=7261481

**Source PDF sha256.** `78c42db521624f7398717732a7fa51a6e3157a5adf02a2e09fbab15e0cf920d9`

**Evidence level.** complete public 30-page arXiv v2 manuscript of a peer-reviewed journal article with exact PDF SHA-256, page-bound passages, arXiv identity, and Crossref identity

**Mapping review tier.** independent substantive scholarly-growth qualification

**Mapping confidence.** 0.97  **Mapping ambiguous.** false

**Topics.** research-methods, ai-and-agents, reputation, scholarly-growth-coverage, scholarly-literature, provenance, privacy, selective-disclosure, computational-workflows

**Provenance.** Affirmed in kaal-review:2026-08-13:scholarly-growth-7261481-023-reviewed-v1 at https://wulfkaal.github.io/positions/by-claim/7261481-023.html.

**Record type.** This is a dated commentary position that extends a scholarly corpus claim. It is not a verbatim claim extracted from the paper.

**Canonical form.** This markdown file is the canonical hashed representation of the position.