I introduce process topology as a formal framework for assessing the trustworthiness of verified knowledge from the structural properties of its production process alone, independent of the content of any specific claim. The framework rests on a simple observation: knowledge produced through genuinely independent verification leaves a different statistical signature in metadata than knowledge produced through coordinated or captured verification processes. These signatures — patterns in validator participation, temporal dynamics, challenge distributions, and correlation structures — are computable from public Verified Causal Structure (VCS) metadata without requiring knowledge of ground truth for any individual claim. We formalize process topology as a measurable property of verification records with explicit ties to compound verification depth (CVD), trajectory events (negative knowledge), and the Generation Ledger. We prove a distinguishability theorem for naive adversary models, identify the limits of detection against sophisticated adversaries (whose calibration costs are raised by the Generation Ledger, slashing mechanics, and challenge bonds), and describe specific detection mechanisms implementable over the live AetherNet testnet APIs. We argue that process topology constitutes the meta-epistemic accountability layer of the three-layer epistemic substrate (causal structure, structural independence, economic incentive alignment) formalized in the Epistemic Substrate Thesis, enabling distributed, permissionless auditing of verification integrity. Keywords: process topology, verification metadata, VCS, capture detection, epistemic accountability, meta-epistemic measurement, structural transparency, trajectory events, coordinated behavior detection
Michael Schreiber (Fri,) studied this question.