📘 r_Scaffold.md
Radiology Module Scaffold — TriadicFrameworks Canon#
1. Canonical Metadata#
ai.module: Radiology
ai.version: 1.0
ai.purpose: Radiology subsystem identity + canonical context
ai.keywords: radiology, drift, coherence, contrast, vmri-lite, capture
ai.module.name: r_Scaffold
ai.module.summary: Canonical scaffold for the Radiology module.
ai.module.category: Applied Medicine
2. Session Context#
context-label: Canon
context-value: TriadicFrameworks
context-label: Modules
context-value: Radiology, Medicine, Drift, Coherence, Contrast, VMRI, NIST
context-label: Drift
context-value: Temporal + spatial signal change across captures
context-label: Coherence
context-value: Stability vs collapse of tissue signal
context-label: Contrast
context-value: Chemical behavior (uptake, washout, toxicity)
context-label: Format
context-value: Identity + Context + Grammar + Operators
context-label: Front door
context-value: r_Scaffold.md
context-label: Audience
context-value: Radiologists, students, AI models
3. Badge#
[🩻 Radiology Module — Canonical Scaffold]
4. Module Identity#
Radiology is the TriadicFrameworks subsystem responsible for:
- interpreting medical imaging using RTT grammar
- quantifying drift, coherence, and contrast
- attaching resonance profiles
- running VMRI‑Lite predictive simulations
- generating RTT overlays for teaching and AI
Radiology is the visibility engine of TriadicFrameworks.
5. Grammar Summary#
Radiology uses five grammar layers:
Capture Grammar#
- CAPTURE
- FIELD
- LAYER
- SIGNAL
- NOISE
- DRIFT‑SIGNAL
- COHERENCE‑SIGNAL
Drift Grammar#
- DRIFT
- DRIFT‑VELOCITY
- DRIFT‑VECTOR
- DRIFT‑ZONE
- DRIFT‑BURST
- DRIFT‑DECAY
- DRIFT‑NOISE
- DRIFT‑MAP
Coherence Grammar#
- COHERENCE
- COHERENCE‑FIELD
- COHERENCE‑BREAK
- COHERENCE‑RESTORE
- COHERENCE‑MAP
- COLLAPSE‑RISK
Contrast Grammar#
- UPTAKE
- WASHOUT
- ENHANCEMENT‑ZONE
- FALSE‑UPTAKE
- FALSE‑WASHOUT
- TOXICITY‑CORRIDOR
VMRI Grammar#
- SIM‑START
- SIM‑VARIANT
- SIM‑CORRIDOR
- SIM‑PASS
- SIM‑FAIL
- SIM‑OPTIMAL
6. Operator Summary#
Radiology operators are grouped by layer:
Capture Operators#
op_field, op_layer, op_signal, op_noise,
op_drift_signal, op_stability, op_enhancement,
op_resonance_attach, op_resonance_predict,
op_vmri_lite, op_overlay
Drift Operators#
op_drift, op_drift_velocity, op_drift_vector,
op_drift_zone, op_drift_burst, op_drift_decay,
op_drift_noise, op_drift_map, op_drift_profile,
op_drift_predict, op_drift_overlay
Coherence Operators#
op_coherence, op_coherence_field, op_coherence_break,
op_coherence_restore, op_coherence_map,
op_coherence_profile, op_coherence_predict,
op_coherence_collapse, op_coherence_overlay
Contrast Operators#
op_uptake, op_washout, op_enhancement_zone,
op_false_uptake, op_false_washout,
op_toxicity_corridor, op_contrast_profile,
op_contrast_predict, op_contrast_map,
op_contrast_overlay
VMRI Operators#
op_vmri_start, op_vmri_variant, op_vmri_batch,
op_vmri_corridor, op_vmri_pass, op_vmri_fail,
op_vmri_optimal, op_vmri_contrast_predict,
op_vmri_tissue_predict, op_vmri_profile,
op_vmri_overlay
7. Canonical Radiology Pipeline#
CAPTURE → FIELD → LAYER → SIGNAL
→ DRIFT → COHERENCE → CONTRAST
→ RESONANCE → VMRI
→ OVERLAY
This pipeline governs every RTT‑Radiology analysis.
8. Pantheon Anchor#
Radiology’s mythic entities:
Void#
Aetherium • Nullis • Quietus
Shadow#
Umbros • Vespera • Fractura
Clarity#
Lucerna • Radiantus • Harmona
Titans#
Tomographos (CT) • Magneta (MRI) • Sonara (US) • Fluorion (PET)
Liminal Spirits#
Iodina • Gadolina • Bariuma • Fluorix
Statera • Vectora • Corridora
These entities help students conceptualize imaging as a dynamic, mythic system.
9. DOC_MAP#
r_Capture.md
r_Drift.md
r_Coherence.md
r_Contrast.md
r_VMRI.md
r_Overlays.md
r_Index.md
r_Pantheon_Profile.md
r_Glyphs.md
r_Scaffold.md
r_Student_Guide.md
r_Tricorder.md
Scaffold Ready#
Your Radiology scaffold page is now complete, canon‑aligned, and ready for GitHub.
