InterstellarCore.SensorPack v1.0 — Unified Z0–Z6 Monitoring Dashboard

Mode: Almost-Code (Canonical Monitoring Module)
Purpose: Detect drift early, enforce Rate-Dominance, protect BaseFloor, and gate GeniusCorridor safely.

0) AI Ingestion Lock

			
ID: InterstellarCore.SensorPack.v1.0
Type: Canonical.SensorModule
Scope: Z0–Z6
Dependencies:
- InterstellarCore.Runtime.v1.0
- BudgetRules.v1.0
- P0toP3.TransferProtocol.v1.0
- GeniusCorridor.v1.0
- FenceOS + APRC
Core Law: RepairRate ≥ DriftRate
Trigger Logic: FenceOS-based truncation when thresholds crossed
Vocabulary: Frozen

		

1) Classical Foundation Block

			
What is not measured drifts.
What drifts under load collapses.
What collapses without early truncation spreads.
A civilisation-grade system must:
- detect instability before visible failure
- distinguish noise from structural drift
- act before collapse modes trigger

		

2) Sensor Architecture Overview

			
Sensor Layers:
Z0 — Individual Phase Stability
Z1 — Cohort Phase Shear
Z2 — Institutional Pipeline Continuity
Z3 — Curriculum Integrity
Z4 — Career Corridor Fit
Z5 — BaseFloor + EdgeBandwidth Stability
Z6 — Frontier Output Validation

		

Each layer feeds ChronoHelmAI.

3) Z0 — Individual Sensors (Core Transfer Engine)

3.1 Timed Stability

			
ID: Sensor.Z0.TimedStability
Definition:
Performance under time pressure.
Threshold:
If 2 consecutive timed collapses → trigger FenceOS review.

		

3.2 Backlog Growth

			
ID: Sensor.Z0.Backlog
Definition:
Accumulated prerequisite gaps.
Threshold:
If backlog slope > 0 across 2 cycles → enter Stitching loop.

		

3.3 Transfer Rate

			
ID: Sensor.Z0.TransferRate
Definition:
Success on novel-but-related tasks.
Threshold:
If success < baseline despite rote success → R1 corridor required.

		

3.4 Variation Tolerance

			
ID: Sensor.Z0.VariationTolerance
Definition:
Stability across context shifts.
Trigger:
Collapse under variation → no P3 promotion.

		

3.5 Language Precision

			
ID: Sensor.Z0.LanguagePrecision
Definition:
Clarity + compression of explanation.
Use:
Gate to GeniusCorridor eligibility.

		

4) Z1 — Cohort Sensors

4.1 Phase Shear

			
ID: Sensor.Z1.PhaseShear
Definition:
Variance of phase levels under identical task.
Threshold:
Shear widening rapidly → teacher bandwidth imbalance → reallocate B_repair.

		

4.2 Repair Bandwidth

			
ID: Sensor.Z1.RepairBandwidth
Definition:
Repair time available per learner.
If insufficient:
RepairRate < DriftRate risk.

		

5) Z2 — Institutional Sensors

5.1 Pipeline Continuity

			
ID: Sensor.Z2.PipelineContinuity
Definition:
Quality of handover across levels/teachers.
Break signal:
Sudden backlog spikes at transitions.

		

5.2 Attrition Velocity

			
ID: Sensor.Z2.AttritionVelocity
Definition:
Rate of P2→P1 or P1→P0 slides across cohorts.
If slope rising → Slow attrition mode.

6) Z3 — Curriculum Sensors

6.1 Sequence Integrity

			
ID: Sensor.Z3.SequenceIntegrity
Definition:
Correct prerequisite order.
Signal:
Repeated identical misunderstanding across cohort → structural mis-sequencing.

		

6.2 Assessment Alignment

			
ID: Sensor.Z3.AssessmentAlignment
Definition:
Does assessment measure corridor width or rote memory?
If timed novelty collapses despite high scores → misalignment.

7) Z4 — Career Corridor Sensors

7.1 Corridor Fit

			
ID: Sensor.Z4.CorridorFit
Definition:
Challenge-skill match index.
Signal:
P3 graduates in P1 roles long-term → phase shear and drift.

		

8) Z5 — National Stability Sensors

8.1 BaseFloor Index

			
ID: Sensor.Z5.BaseFloor
Definition:
Minimum stable P2 proportion across population.
If BaseFloor < Floor → freeze GeniusLane expansion.

8.2 Edge Bandwidth Stability

			
ID: Sensor.Z5.EdgeBandwidth
Definition:
Size + sustainability of GeniusCorridor.
If rising while BaseFloor falls → Cannibalisation risk.

9) Z6 — Frontier Output Sensor

			
ID: Sensor.Z6.FrontierOutput
Definition:
Validated new tools/models/methods from GeniusLane.
Must:
Return artefacts to CivP3 base.
If no artefact return:
Reduce B_edge next cycle.

		

10) Collapse Mode Detection Matrix

			
If sudden multi-layer sensor spike → Amplitude/KO collapse
If slow backlog growth across Z0–Z3 → Slow attrition
If timed stability collapse across cohort during crunch → Fast attrition

ChronoHelmAI auto-classifies collapse type.

11) Trigger Logic (FenceOS Integration)

			
IF TimedStability collapses twice → Truncate high load
IF Backlog slope rising → Stitch prerequisites
IF BaseFloor falls below threshold → Reallocate B_edge to B_repair
IF Edge outputs absent 2 cycles → Reduce GeniusLane capacity
IF PhaseShear widens beyond bound → Split lanes and recalibrate

		

12) Minimal Dashboard Schema

			
For each cycle:
Z0:
- TimedStability
- Backlog
- TransferRate
- VariationTolerance
- LanguagePrecision
Z1:
- PhaseShear
- RepairBandwidth
Z2:
- PipelineContinuity
- AttritionVelocity
Z3:
- SequenceIntegrity
- AssessmentAlignment
Z4:
- CorridorFit
Z5:
- BaseFloor
- EdgeBandwidth
Z6:
- FrontierOutput

		

ChronoHelmAI reads:

slopes (Δ)
thresholds
collapse classification
budget adjustments

13) Compact Failure Trace

			
No sensors →
Drift undetected →
Repair delayed →
Slow attrition →
Fast collapse under load →
BaseFloor drops →
Elite destabilised →
System credibility collapses

		

14) Short Publish Block

			
InterstellarCore.SensorPack v1.0 ensures:
- Drift is detected before collapse
- BaseFloor remains protected
- GeniusLane remains bounded
- RepairRate dominance is enforced
- Collapse modes are classified early

		

Version Lock

			
All InterstellarCore deployments must include SensorPack v1.0.
Without real-time Z0–Z6 monitoring,
InterstellarCore is non-operational.

If you say Next,
I will design:

InterstellarCore.ControlTower v1.0 — The full AI + Human hybrid runtime architecture (ChronoHelmAI orchestration layer).

That will unify everything we built into one executable governance system.