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Research-Stack/6-Documentation/docs/ENE_SCHEMA.md

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ENE Substrate: Technical Specification & Schema

Status: PROJECT DATA / REFERENCE
Cross-reference: BRAIN_AS_MANIFOLD.md, FPGA_WARDEN_NODE_SPEC.md

1. Overview

The Effective Neural Engine (ENE) Substrate is a meta-topological storage system designed to map knowledge domains into a hyperbolic semantic manifold. Unlike traditional relational databases, ENE treats data as "packages" with specific settlement states and semantic vectors.

2. Primary Schema: packages Table

The core of the system is the packages table in data/substrate_index.db.

Field Type Description
pkg TEXT Unique identifier (Namespace/Name).
version TEXT ISO-8601 version string.
tier TEXT Epistemic layer: CORE, INFRA, RESEARCH.
domain TEXT Knowledge domain (e.g., neural_manifold).
archetype TEXT Content class (e.g., chat_session, spec).
description TEXT Human-readable snippet or summary.
tags JSON Array of strings for discovery.
source TEXT Provenance identifier (e.g., YourAIScroll).
sha256 TEXT Content integrity hash.
indexed_utc TEXT Ingestion timestamp.
concept_anchor JSON The Lineage Tag. Tracks the idea's "Settlement State".
concept_vector JSON 14-dimension coordinate in the hyperbolic manifold.
idea_weights JSON Conceptual density scores (0.0 - 1.0).
analog_map JSON Pre-computed local analog translations between domains.

3. The Concept Anchor (Lineage)

The concept_anchor tracks how "settled" an idea is. All imports from YourAIScroll default to SEED.

Resolution Levels:

  • SEED: Raw intuition, undefined edges.
  • FORMING: Actively developing, shifting boundaries.
  • STABLE: Well understood, theoretical framework complete.
  • CRYSTALLIZED: Fully settled, ready for manifold compression.
  • COMPRESSED: Encoded into core DSP/FPGA logic via the Manifold-Blit Operator (\oplus).

4. Manifold Geometry

ENE assumes a hyperbolic geometry (K < 0) for semantic storage.

  • Direction = Meaning: The direction of the concept_vector encodes the semantic cluster.
  • Magnitude = Activation: Magnitude represents the conceptual importance or activation frequency.

4.1 Semantic Axis Mapping (14D)

The vector space follows a \phi^{-i} weighted axis scaling (Axis 0 = 1.0, Axis 13 \approx 0.002).

Axis Weight (\phi^{-i}) Semantic Focus
0 1.000 Substrate / Entropy / Foam (General Existence)
1 0.618 Compression / Information Theory
2 0.382 Physics / Thermodynamics / Energy
3 0.236 Neural / Cognitive / Manifold
4 0.146 Formalization / Lean / Logic
5 0.090 Markets / Economic / MEV
6 0.056 Safety / Alignment / Audit
7 0.034 Attestation / Provenance / Cryptography
8 0.021 Hardware / FPGA / Warden
9 0.013 Signal / DSP / Carriers
10 0.008 Synthesis / Bioinfo / DNA
11 0.005 Decisions / Pathing / Planning
12 0.003 Archive / Historical / Lineage
13 0.002 Sovereignty / Identity / Self

5. Plugin Integration (YourAIScroll)

The POST /ingest endpoint bridges external AI insights into this substrate.

  • Targeting: Use "target": "ene" in the payload.
  • Auto-Mapping: Titles are slugified into aiscroll/ package names.
  • Default Tier: All browser exports are assigned the RESEARCH tier.

6. Linear-ENE Bridge

Every ENE ingestion via the /ingest endpoint automatically creates a tracking issue in your Linear project space.

  • Traceability: The Linear Issue URL is stored in the session_id column of the packages table.
  • Context: The issue description contains a reference back to the ENE package name.
  • Settlement Control: Use Linear to track the evolution of a SEED concept as it moves toward CRYSTALLIZED status.

7. Protocol Inheritance Law

...

  • Distributed Availability: Once verified, the protocol becomes a first-class citizen of the manifold, available for local execution on any node without further attestation.

8. $\varphi$-Weighted Manifold Flag Sort

The system uses a 3-way partition logic to autonomously order research trajectories based on their Metatyping Invariant (\Sigma).

Flag Condition (\Sigma) Technical Regime
Red Flag \Sigma < 4.0 DRIFT: Unlawful or noisy signal; quarantined.
White Flag 4.0 \le \Sigma < 10.0 FORMING: Questionable but potentially interesting; review required.
Blue Flag \Sigma \ge 10.0 CRYSTALLINE: Verified truth; stable in the manifold.
  • Topological Pivot: The partitioning threshold is derived from the Golden Stratum Gate (\phi).
  • Recursive Depth: Within the Blue Flag group, data is further sorted along the 14 axes of the manifold.

9. Thermodynamic N-Space Partition (Landauer Sort)

Replacing the purely mathematical heuristic (\phi), the system utilizes a Universal Physical Constant—the Boltzmann Constant (k_B) via the Landauer Limit (W \ge k_B T \ln 2)—to physically partition the N-space based on Informatic Stress and entropy generation.

Thermodynamic Flag Substrate State Technical Regime
Dissipative High Entropy Loss UNLAWFUL: Fails the Landauer bound; quarantined.
Reversible Adiabatic Shift REVIEW: Marginal energy cost; requires proof.
Landauer Optimal Coherence VERIFIED: Hits the physical limit of efficiency; stable.
  • Physical Grounding: By mapping trajectory quality (\Sigma) to thermodynamic depth, the system ensures that data ordering is not just mathematically sorted, but constrained by the fundamental energy limits of computation.

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