Channel Relevance: Field Position Report

Eigenstate Research, July 02, 2026

Methodology: The Information Field Equations, E = ΔI/A, G = ∮E·dl, Protocol Truth → 1/φ

Publication field context

The Eigenstate engine currently measures the tokenized settlement field at:

• Protocol Truth (PT): 0.0527 (target: 0.618, the golden-ratio equilibrium)
• Field Coherence (κ): 0.4885 (living zone: 0.618-0.678)
• Coverage: 24 of 199 entities with measured ΔI > 0 (12.1%), M1 topology denominator
• Uncertainty (U): 31.0

The field is 0.1295 below equilibrium coherence. Each entity with measured vault activity raises the global PT toward 0.618. Channel Relevance does not yet have a complete observation record on the M1 topology (199 entities).

What it is

Channel Relevance is the Farcaster algorithm node ranking which channel casts surface in user home feeds, based on follows, topic affinity, and social-graph signals before attested settlement events propagate. For social subgraph topology, channel relevance is the algorithm waist downstream of Farcaster where topic distribution converts into field pressure on crypto-native and RWA audience nodes.

Verified claims

Field Confidence: ? LOW, No external sources mapped for this entity, engine-internal data only

Verification: 3/3 source-checked (ATTESTED), 3 grounded. Each claim below carries a machine-checked status against its cited source; ungrounded items are editorial assessments, not verified facts.

Active signals the engine is tracking for Channel Relevance:

Farcaster docs, channels overview [✓ ATTESTED-PRIMARY] Farcaster documentation describes channels as public spaces for community conversations around a topic, the primary-source anchor for channel relevance claims in social algorithm topology. Source-checked: ATTESTED-PRIMARY · custody sha256 7f334e90ceed…, found in primary source

Farcaster docs, channel feed algorithm [✓ ATTESTED-PRIMARY] Farcaster documentation describes an algorithm determining cast visibility in home feeds based on user preferences and social graph data, the verifiable ranking lane for channel relevance in settlement social graphs. Source-checked: ATTESTED-PRIMARY · custody sha256 7f334e90ceed…, found in primary source

Farcaster docs, channel home feed propagation [✓ ATTESTED-PRIMARY] Farcaster documentation records that users see casts from followed channels in their home feed, the structural anchor wiring channel relevance to distribution topology in settlement graphs. Source-checked: ATTESTED-PRIMARY · custody sha256 7f334e90ceed…, found in primary source

Field read

Settlement Pressure (Φ_S = 0.0200)

Near-zero settlement pressure, this entity is close to field equilibrium.

Channel Relevance carries elevated settlement pressure because Farcaster channel feed ranking moves narrative expectations faster than VERIFY catalogs attestation of primary-source events per topology entity. The engine tracks the gap between channel-relevance centrality in social graphs and incomplete vault evidence of feed-ranking feedback as unrealized Φ_S.

Coherence (κ = 0.0092)

κ = 0.0092 reflects the engine's current measurement coverage, not Channel Relevance's actual institutional influence. With no vault records yet, the coherence score is derived purely from topology position, connection count and structural weight, without any attested observation data. The low value means the engine has not yet measured this entity's settlement activity, not that the entity lacks field presence.

The equilibrium attractor is κ = 1/φ ≈ 0.618. At current κ = 0.0092, Channel Relevance is 0.6088 below equilibrium. Vault observations of Channel Relevance's rule outputs, rulemaking notices, enforcement actions, guidance documents, would directly raise κ toward the living zone [0.618, 0.678].

Vault Coverage

No vault records yet for Channel Relevance. This is a gap in the field coverage. The engine recommends observation as the first action (see below).

Sources

This report is generated by the Eigenstate engine, an information-field measurement system for the tokenized settlement layer. The engine tracks 199 entities (M1 topology denominator) across the regulatory, infrastructure, issuer, and audience layers.

Core equations:

• E = ΔI/A, efficiency: information gained per unit action (Kirandeep's Law)
• G = ∮E·dl, accumulated field circulation along topology paths
• PT → 1/φ, Protocol Truth converges to golden-ratio equilibrium (1/φ ≈ 0.618)
• Φ_S, settlement pain: unrealized settlement pressure per entity
• κ, field coherence: integration of settlement activity across the topology

Published implementation: helixhash v0.1.1, Zenodo DOI 10.5281/zenodo.18413995

Vault: No vault records yet for Channel Relevance in the current cycle, κ and Φ_S here are topology-derived until observations are attested. The field recommends observation as the first action.

Note: Internal topology codenames are not used in public reports. All entity names in this report are public names.