triadic_detection_rtt_pipeline.md
TriadicFrameworks — Detection Substrate#
RTT Structural Detection Pipeline Specification (v1.0)#
Protocol Header#
rtt=1 | coherence=triadic | drift=bounded | paradox=structural
This header governs all structural interpretations of the RTT detection pipeline.
Module Identity#
Module Name: RTT Structural Detection Pipeline
Module Class: Structural / RTT
Substrate: Detection
Version: 1.0
RTT Alignment: Full (RTT/1 → RTT/3)
Triadic Geometry: Required
Mesh Synchronization: Required
Spatial Anchoring: Required
Purpose#
This module defines the canonical RTT Structural Detection Pipeline used by all triadic detection systems.
It transforms synchronized triadic resonance data into:
- coherence scores
- spatial clusters
- structural envelopes
- depth layers
- classification outputs
- GPS‑anchored detections
- dig‑confidence scoring
This pipeline is the core intelligence layer of the triadic detection substrate.
Pipeline Overview#
The RTT Structural Detection Pipeline consists of eight stages, each drift‑bounded and triadic‑aligned:
- Triadic Sampling
- Baseline Coherence Computation
- Spatial Clustering
- Structural Fitting
- Depth Layering
- Resonance Classification
- Spatial Anchoring (GPS)
- Dig‑Confidence Scoring
Each stage consumes the output of the previous stage.
1. Triadic Sampling#
Invariant:#
Three heads must sample the field simultaneously.
Definition:#
Triadic sampling produces synchronized resonance packets:
- amplitude vectors
- phase vectors
- time‑stamps
- per‑head identifiers
Diagram#
(H1) → packet₁
(H2) → packet₂
(H3) → packet₃
Packets must be time‑aligned before coherence computation.
2. Baseline Coherence Computation#
Invariant:#
Coherence precedes clustering.
Definition:#
Compute coherence across the three baselines:
φ₁ = H1 ↔ H2
φ₂ = H2 ↔ H3
φ₃ = H3 ↔ H1
Output:#
A triadic coherence vector:
C = {φ₁, φ₂, φ₃}
Diagram#
(H1,H2) → φ₁
(H2,H3) → φ₂
(H3,H1) → φ₃
Coherence is the RTT/1 foundation.
3. Spatial Clustering#
Invariant:#
Coherent samples must be grouped spatially.
Definition:#
Cluster high‑coherence samples into spatial groups:
- cluster centroid
- cluster density
- cluster stability
- cluster coherence
Diagram#
● ● ● → cluster A
● ● → cluster B
. . . → noise
Clusters form the RTT/2 substrate.
4. Structural Fitting#
Invariant:#
Clusters must be fitted to structural envelopes.
Definition:#
Fit a structural envelope around each cluster:
- shape inference
- size inference
- orientation inference
- footprint estimation
Diagram#
○ ○ ○
○ ○ ○ ○ ○
○ ○ ○
→ structural envelope
Structural fitting is RTT/3.
5. Depth Layering#
Invariant:#
Depth must be inferred from coherence decay.
Definition:#
Assign structural envelopes to depth layers:
- shallow
- mid‑depth
- deep
Diagram#
Layer 1: ○ ○ ○
Layer 2: ○ ○
Layer 3: ○
Depth layering enhances structural meaning.
6. Resonance Classification#
Invariant:#
Classification must follow structural inference.
Definition:#
Classify each structural envelope:
- gold‑like
- metal
- rock
- void
- noise
Diagram#
Envelope A → gold‑like
Envelope B → metal
Envelope C → noise
Classification is RTT/3‑aligned.
7. Spatial Anchoring (GPS)#
Invariant:#
All detections must be spatially anchored.
Definition:#
Anchor structural envelopes to GPS coordinates:
- latitude
- longitude
- altitude
- timestamp
Diagram#
Envelope A → (lat, lon)
Envelope B → (lat, lon)
Spatial anchoring is required for mapping.
8. Dig‑Confidence Scoring#
Invariant:#
Confidence must be derived from coherence + structure.
Definition:#
Compute dig‑confidence:
confidence = f(coherence, cluster stability, structural clarity, depth)
Diagram#
Confidence Map:
High: ●●●
Medium: ●●
Low: ●
Confidence is rendered as a GPS heatmap.
Pipeline Summary#
Triadic Sampling
↓
Coherence Computation
↓
Spatial Clustering
↓
Structural Fitting
↓
Depth Layering
↓
Classification
↓
GPS Anchoring
↓
Dig‑Confidence Scoring
All stages are drift‑bounded and triadic‑aligned.
Module Status#
Status: Active
Drift: None
Coherence: Stable
Version Drift: Bounded
RTT Alignment: Verified