Start5 · Technology & reproducibility5.1 · Documentation & traceability
Content status: 24 August 2026Website 2.2.2
DOCUMENTATION

A result becomes reviewable only when its path of origin remains visible.

Documentation is not an appendix written at the end of the project. It is part of the system. For a material finding, a reviewer should be able to see five things: which data were used, which rules applied, which version was calculated, under which conditions the test ran, and what limits follow from those conditions.

Public layer: clear interpretationDeeper layer: technical and methodological evidence
DOCUMENTATION

A reader should be able to understand how a statement was produced.

A robust result requires more than the number itself: data state, calculation and decision rules, system version, test conditions and known limitations all matter. The documentation is intended to make that chain visible from the published finding back to its underlying basis.

FIVE QUESTIONS

What a reader should be able to establish for every important claim

01

Which data?

Period, instruments, frequency, provenance, quality status and, where relevant, licensing or usage conditions.

02

Which rules?

Decision rules, parameters, filters, execution assumptions and risk logic must belong to a defined rule state.

03

Which version?

A rule change creates a new state. Results from different versions should not be silently combined.

04

Which test?

Test period, control group, comparison path, cost assumptions and other conditions determine what the number actually means.

05

Which limitation?

Every finding should state what has not yet been tested – such as intraday ordering, costs, new data or isolated APS impact.

EXAMPLE

From a published statement back to the test basis

The evidence page, for example, states the scope of the Version 1 test matrix. That number alone would be of little value. The documentation chain gives it meaning: 94 real instruments were evaluated with 60 oscillators under the same basic logic, producing 5,640 systematically executed individual tests.

The context also states that these tests share market, data and formula families and therefore must not be treated as 5,640 independent scientific experiments. Those details prevent a correct number from producing an incorrect conclusion.

Published statement5,640 systematically executed individual tests
Definition94 real instruments × 60 oscillators
Data & test stateVersion 1 · historical daily data 2009–2025
Limitationbroad test matrix · not 5,640 independent experiments
STATUS, NOT A LABEL

Not everything is described with the same word “validated”.

A historical comparison, a documented test and an independent replication are different evidence states. The site therefore uses visible status labels.

Documented

The statement can be traced in the current source or test base.

Historical finding

The number or observation exists, but is not presented as universal performance evidence.

Revalidation required

The finding is intended to be reproduced or isolated under Version 2 conditions.

Planned

The function or test belongs to the target architecture but is not yet a finished component.

DOCUMENTATION AS PART OF THE PRODUCT

Domain knowledge, code and evidence should describe the same version.

A future user or acquirer should not find contradictory system states in marketing material, source code and manuals. The long-term objective is a coherent chain of domain documentation, technical architecture, test records, user help and version history.

Domain documentation

What the rules mean, why they exist and which market or risk situation they represent.

Technical documentation

How modules, data models, interfaces, error handling and operating conditions are implemented.

Test & audit records

Which version was run, when, on which data and whether the expected reference output was reproduced.

Help & explanation

Contextual assistance for users – ultimately in German and English and ideally available inside the product.

AI & DOCUMENTATION

AI may support documentation, but it must not invent an unreviewed new system state.

Generative AI can search large knowledge bases, structure text, formulate explanations and assist quality assurance. Precisely because it can do so, it needs explicit sources, versions and approval rules. AI-generated wording is not a new domain standard until it has been checked against the documented system logic.

Source-groundedMaterial domain claims are tied back to existing documentation and test states.
Editorially reviewedPublished content is not copied from an AI draft without review.
Version-consistentNew wording must not silently change the underlying system state.
REVIEW

The evidence page applies this principle to concrete metrics.

FROM DOCUMENTATION TO EVIDENCE

The Evidence Map shows how this documentation principle is applied to public statements.

For every core claim it makes the metric, current support, methodological limitation and next validation step visible.

Public evidence trail

A number should not merely be readable. A reviewer should be able to see why it appears on the website and which test would change its status.

View Evidence Map →