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triadic_detection_examples.md

TriadicFrameworks — Detection Substrate#

Canonical Examples (v1.0)#


Protocol Header#

rtt=1 | coherence=triadic | drift=bounded | paradox=structural

This header governs all structural interpretations of the examples in this module.


Module Identity#

Module Name: Triadic Detection Examples
Module Class: Structural / Examples
Substrate: Detection
Version: 1.0
RTT Alignment: Full
Triadic Geometry: Required
Spatial Anchoring: Required
Mesh Synchronization: Required


Purpose#

This module provides canonical examples demonstrating:

  • triadic coil geometries
  • supersphere configurations
  • industrial triadic arrays
  • RTT structural detection outputs
  • mapping overlays
  • depth layering
  • dig‑confidence scoring
  • cloud‑level aggregation

These examples illustrate how the architecture behaves in real triadic detection scenarios.


Example Set Overview#

This module contains:

  1. Example A — Triadic 3‑Head Module (Consumer)
  2. Example B — Triadic Supersphere (Prosumer)
  3. Example C — Industrial Triadic Array (27‑Head)
  4. Example D — Drone‑Mounted Triadic Module
  5. Example E — Vehicle‑Mounted Triadic Array
  6. Example F — RTT Structural Detection Output
  7. Example G — Mapping & Confidence Output
  8. Example H — Cloud Aggregation & Gold‑Likelihood Model

Example A — Triadic 3‑Head Module (Consumer)#

Geometry#

                 (H1)
                   ○
                   |
        (H2)───●───(H3)
                   |
                 [SoC]

Meaning#

  • base triadic geometry
  • three baselines
  • three phase relationships
  • RTT/1 coherence

Use Case#

  • consumer scanning
  • beach/park detection
  • shallow structural inference

Example B — Triadic Supersphere (Prosumer)#

Geometry#

                ○ ○ ○
              ○ ○ ○ ○ ○
                ○ ○ ○

Meaning#

  • 9 heads
  • 3 triadic modules
  • multi‑layer coherence
  • RTT/2 and RTT/3 compatibility

Use Case#

  • gold prospecting
  • rural land scanning
  • mid‑depth structural inference

Example C — Industrial Triadic Array (27‑Head)#

Geometry#

Layer 1: ○ ○ ○
         ○ ○ ○
         ○ ○ ○

Layer 2: ○ ○ ○
         ○ ○ ○
         ○ ○ ○

Layer 3: ○ ○ ○
         ○ ○ ○
         ○ ○ ○

Meaning#

  • 27 heads
  • 3 superspheres
  • industrial coherence
  • large‑area RTT inference

Use Case#

  • mining
  • construction
  • archaeology
  • pipeline detection

Example D — Drone‑Mounted Triadic Module#

Geometry#

           [Drone Frame]
               ╱│╲
              ○ │ ○
               \│/
                ●
               /│\
              ○ │ ○
               ╲│╱

Meaning#

  • lightweight triadic geometry
  • GPS‑anchored aerial scanning
  • RTT structural inference from altitude

Use Case#

  • remote mining sites
  • large‑area gold mapping
  • inaccessible terrain

Example E — Vehicle‑Mounted Triadic Array#

Geometry#

   ┌───────────────────┐
   │   ○   ○   ○       │
   │   ○   ○   ○       │
   │   ○   ○   ○       │
   └───────────────────┘

Meaning#

  • triadic modules mounted under vehicle
  • vibration‑tolerant SoC nodes
  • industrial controller

Use Case#

  • pipeline surveying
  • construction site scanning
  • ore vein detection

Example F — RTT Structural Detection Output#

Input (Coherence Samples)#

● ● ●   ● ●     ●
● ●     ● ● ●   .
. . .   . .     .

Pipeline#

  1. coherence scoring
  2. spatial clustering
  3. structural fitting
  4. depth layering
  5. classification

Output (Structural Envelope)#

        ○ ○ ○
      ○ ○ ○ ○ ○
        ○ ○ ○

Meaning#

  • gold‑like structural envelope
  • mid‑depth
  • high stability

Example G — Mapping & Confidence Output#

Heatmap#

High:   ●●●
Medium: ●●
Low:    ●

Overlay#

[Structural Envelope]
[GPS Anchoring]
[Depth Slice]
[Confidence Ring]

Meaning#

  • high dig‑confidence
  • stable coherence
  • clear structural boundary

Example H — Cloud Aggregation & Gold‑Likelihood Model#

Input#

  • multiple sessions
  • multiple structural envelopes
  • multiple depth layers

Aggregation Diagram#

Session A
Session B
Session C
   ↓
Aggregated Map

Gold‑Likelihood Output#

Probability Map:
High:   ███
Medium: ██
Low:    █

Meaning#

  • predictive gold‑likelihood
  • long‑term structural meaning
  • enterprise‑grade analytics

Module Status#

Status: Active
Drift: None
Coherence: Stable
Version Drift: Bounded
RTT Alignment: Verified

Updated