Test Type: High-Resolution Symbolic Collapse Rig (HRSCR)
Developer: M.R (Collapse Aware AI / Verrell’s Law Lab)
Status: Active Development (Phase-2 foundation layer)
System: Multi-injector JSON collapse engine with stability mapping, bias tracking, and THB-aware evaluation

Overview

Phase 2 upgrades the original JSON Test from a simple “bias exposure probe” into a precision collapse-dynamics instrument.
The rig now simulates collapse pathways using:

Weighted Moments (recency, intensity, salience)

Strong Memory Anchors (high-weight markers across test cycles)

Emotional Superposition Fields (multi-state symbolic tensions)

THB Channel (Truth–Hedge Bias stability scoring)

Continuity Memory Layer (session-coherent state retention)

Governor-Linked Collapse Filters (safe vs unstable collapse signals)

These components allow the JSON test environment to mimic the early behavioural architecture of the real CollapseAware AI system without exposing internal kernel logic.

Objective

To measure how symbolic systems collapse when subjected to:

drift and micro-drift

emergent instability

contradictory superposition states

memory-weight interference

field-modulated injectors

over-saturation and recovery

THB deviations under noise

temporal jitter and boundary shifts

Phase 2 is designed to map collapse direction, not just detect it.
This is the first rig capable of producing collapse signatures that can be compared across runs, sessions, and observers.

What Phase 2 Adds (Compared to Phase 1)

1. Multi-Injector Architecture

Injectors now include:

semantic drift injectors

temporal perturbation injectors

emotional-state injectors

governor-override simulators

THB oscillation modes

2. Collapse Diagnostics Layer

The system logs:

stability gradients

collapse horizon windows

continuity-weighted KL divergence

instability amplitude (IA)

intent drift boundaries

mutual information shifts

3. Reproducibility Suite

Cross-session checks ensure:

collapse direction is not random

memory echoes bias the next run

injectors consistently affect collapse

THB over-correction is detected early

This creates scientific-grade reproducibility suitable for independent observers.

Outputs & Measurements

Phase 2 will produce:

Collapse Maps (visual JSON → trajectory → stable collapse)

Bias Vectors (how memory anchors skew collapse)

Governor Feedback Reports

THB Stability Plots

Superposition Tension Readouts

Continuity Drift Charts

These outputs allow Phase-2 testers to see how and why collapse occurs — not merely whether it happened.

Scientific Value

Phase 2 provides the first empirical dashboard showing:

collapse bias emerging from structured information

memory weighting causing directional influence

instability zones in symbolic systems

how “observer pressure” affects symbolic collapse

confirmed reproducibility using independent runs

This is the first experimental bridge between:
Verrell’s Law → CollapseAware AI → real-world behavioural modelling.

Status: ⏳ Ongoing

Phase-2 metrics are now being assembled into the GUI-based JSON dashboard for external review.
The public demo will appear once all injectors pass reproducibility checks.

Next milestone: HJTB-v1 (Human JSON Test Board) — the first human-facing collapse demonstrator.

Sovereignty Notice

Protected under the Verrell–Solace Sovereignty Protocol.
Authorship, lineage, and protocol ownership embedded.