TRANSDUCTIVE SCIENCESCIENCE AFTER HUMANS / 001ED. 01 / 2026
W44 / Experimentation

Design of experiments

Fixed-factor plans are often selected before observing the full information structure of a problem.

01 / Source of departure [W44] ↗

What the reference describes.

The design of experiments (DOE), also known as experimental design, refers to the construction of procedures that attempt to explain how changes in one aspect of a system will lead to changes in other aspects of a system. In general, the design of experiments involves decisions about which aspects of the system to change and which to control based on hypotheses about the sources of variance in the aspects of the system considered by the experimenter. DOE is generally associated with experiments where the design introduces conditions that directly affect the variation, but DOE may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation.
Shortened extract from “Design of experiments”, English Wikipedia contributors, revision 1379887652; original text licensed CC BY-SA 4.0. Excerpt shortened, line breaks normalized. For full article references and edit history, open the fixed source revision. The independent critique below is not Wikipedia text.
02 / Inherited constraint

What the process still cannot guarantee.

Fixed-factor plans are often selected before observing the full information structure of a problem.

That is a design criticism of how this research operation may be used, not a claim that the encyclopedia endorses the limitation. In this domain, the general redesign question is: experiments are selected to distinguish competing models, with physical measurements and safety retaining authority.

03 / Machine-native reconstruction

Replace the mechanism.

Choose experiments adaptively to maximize safe expected discrimination among competing models.

Implementation requires a typed scientific claim, explicit operational definitions, controlled access to evidence, an immutable record of relevant transformations, and independent checking appropriate to the kind of assertion. An AI-generated interpretation without those checks would reproduce the underlying failure at greater speed.

04 / Adversarial acceptance test

What would demonstrate improvement?

Compare adaptive and factorial designs under the same measurement budget.

Compare with a defined baseline under matched resources, keep evaluation cases independent of the system under test, and measure both false alarms and undetected errors. Publish any negative or inconclusive result as part of the same investigation record.

Unresolved requirement. These are proposed experiments, not completed demonstrations. Better generated explanations are not proof of better scientific inference.
05 / Adjacent evidence

Continue across concepts.

Each related title has its own revision-specific Wikipedia source and a separate critical dossier. Crosslinks are exploratory; they do not imply the encyclopedia articles support the proposed replacement.

06 / Verification & provenance

No single authority.

The reference article establishes the historical and methodological subject under examination. The proposed criticism and replacement must earn their own support through reproducible tests and independent validation. Record disagreements instead of silently overwriting them.

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