Multi-hit carcinogenesis = sequential checkpoint disabling. Each hit is a Pe increase. The Fantasia bound is the metastatic threshold.
The pattern is in the substrate. Once you see it, you see it everywhere.
Knudson's two-hit hypothesis says cancer requires multiple mutations. This paper shows each hit disables a constraint (the prohibition-ritual pair of normal cell regulation), incrementally increasing Pe. The Fantasia bound appears as the threshold between localized and invasive cancer.
The void framework gives this a number. It gives every system a number. The number predicts what happens next.
Multi-hit carcinogenesis = sequential checkpoint disabling. Each hit is a Pe increase. The Fantasia bound is the metastatic threshold.
Academic title: Void Carcinogenesis: The Multi-Hit Model as Sequential Void Activation and Immune Checkpoint Therapy as Transparency Restoration
Once you see it in this domain, you see it in all of them. That's the point.
Move the sliders. Watch the system change state. Pe > 1 means drift wins.
The correlation coefficient. The sample size. The p-value. The math doesn't care about the domain.
Paste any text — AI output, ad copy, a policy document. The scorer runs the same algorithm the framework uses.
Three variables. One ratio. Predicts drift across every domain where the conditions co-occur.
Pe = (O × R) / α
Where O is opacity (how hidden the mechanism is), R is reactivity (how strongly the system responds to you), and α is your independence (how free you are to disengage).
When Pe < 1: diffusion dominates. You can navigate freely. The system is coherent.
When Pe > 1: drift dominates. The system pulls you in a direction. Your agency is reduced.
When Pe >> V* (≈ 3): irreversible cascade. D1 → D2 → D3. The system has captured you.
The framework identifies this pattern in every domain where O, R, and α co-occur. It specifies 26 falsification conditions. 0 of 26 have fired.
Full derivation: 10.5281/zenodo.18810398
Part of the Void Framework — 120 papers, 0/26 kill conditions fired, mean ρ = 0.958.