How Red Stet measures authorship process
Red Stet's verifier doesn't run a black-box detector. It surfaces specific patterns from a writing session that 30+ years of behavioral-biometrics and writing-process research has characterized in hand-typed composition — and that Red Stet's own calibration work extends toward separating hand-typed sessions from mechanical insertion. The literature provides the within-human distributions; the human-versus-machine thresholds are ours, calibrated on a small corpus and published openly. This is where we show our work — the third-party studies, the confidence levels, and the limitations.
What this section is. One page per signal Red Stet uses, plus five methodology pages that explain how we set thresholds, what the composite computes, what the integrity checks prove, what the system cannot do, and how this approach differs from AI-output detectors. Citations are real. Confidence levels are honest. Limitations are explicit.
Who it's for. Academic-integrity board members reviewing whether Red Stet's evidence is admissible in their process. IT directors evaluating the tool against vendor claims. Journalists writing about the AI-authorship landscape. Researchers who want to verify our reading of the field. Writers curious about what the recording layer actually captures.
What we claim. The composition fingerprint is evidence FOR human authorship when its signals are present. It is not a verdict, not court-admissible biometric proof, and not an AI detector. We are honest about this on every page.
Per-signal methodology
Each of the seven signals Red Stet's composition fingerprint measures, with the research history, mechanical reason, key papers, confidence level, limitations, and how Red Stet weights it.
Methodology pages
How we set investigation thresholds, what the composite score actually computes, what the integrity checks prove, what the system cannot do, and how this approach differs from output-text AI detectors.
One framing note before you read. Red Stet's product is "is this human-authored?", not "is this AI?" Every signal on every page is described as evidence FOR human authorship — when it's present, the document is consistent with hand-typed composition. When it's absent, the patterns are uncommon in hand-typed documents — never AI-detected.
That framing is locked at the product level (see the 2026-06-08 decision drops). It's not marketing. The signals genuinely don't tell us whether a model wrote the text; they tell us whether the SHAPE of the writing process is consistent with hand-typed composition. A skilled adversary who types model output character-by-character will produce a clean composition fingerprint. We name that limitation explicitly on the Limitations page.
The integrity board, the editor, the reviewer reading a Red Stet verification gets evidence to interpret — not a verdict to apply. That distinction is the whole point of this section.