MEDICAL_SUBSTRATE_OPERATOR

RTT Operator — Medicine Module#

Substrate Classification • Stability • Layer Interference#

Purpose#

The MEDICAL_SUBSTRATE_OPERATOR identifies and evaluates the substrate of medical information across different regimes.
Medical content is unusually sensitive to substrate because:

• ads distort meaning
• mobile templates reorder clinical logic
• AI overlays introduce dynamic content
• translation layers create semantic drift
• PDF vs HTML changes continuity
• image‑embedded text breaks accessibility

This operator ensures that downstream reasoning (continuity, drift, synthesis) is based on clean, substrate‑aware input.

What This Operator Detects#

1. Substrate Type#

The operator classifies medical content into one of the following:

• html — standard web pages (Cleveland Clinic, NHS)
• mobile_html — mobile‑first, dynamic templates (Ping An)
• pdf — clinical guidelines, static documents
• image — screenshots, infographics, embedded text
• ocr — extracted text from images
• mixed — combinations of the above

This classification is foundational for drift and continuity analysis.

2. Substrate Stability#

Substrate stability measures how likely the substrate is to:

• preserve structure
• preserve meaning
• resist drift
• resist commercial interference
• resist translation distortion

Expected patterns:

3. Substrate Noise#

Noise includes:

• ads
• trackers
• telemedicine prompts
• product suggestions
• AI triage overlays
• SEO‑driven blocks
• mobile‑only reorderings

The operator flags:

• noise_low
• noise_medium
• noise_high

Ping An often triggers noise_high.

4. Substrate Layer Interference#

This detects when substrate layers interfere with medical meaning:

• mobile templates reorder symptom → cause → treatment
• AI overlays inject dynamic suggestions
• translation layers alter phrasing
• ads interrupt clinical flow
• image‑embedded text breaks continuity

The operator flags:

• layer_interference_present
• layer_interference_absent

5. Accessibility Stability#

Accessibility affects structural clarity:

• alt‑text presence
• heading hierarchy
• semantic HTML
• screen‑reader compatibility

NHS is strongest here.
Ping An is weakest.

Inputs#

The operator accepts:

• raw medical pages
• mobile and desktop variants
• PDFs
• images
• OCR text
• AI‑augmented triage overlays

Outputs#

1. Substrate Packet#

A structured metadata output:

{
  "substrate_type": "mobile_html",
  "substrate_stability": "medium",
  "substrate_noise": "high",
  "layer_interference": "layer_interference_present",
  "accessibility_stability": "low"
}

2. Substrate Score (0–1)#

3. Substrate Flags#

• substrate_unstable
• noise_high
• translation_layer_detected
• ai_overlay_detected
• commercial_layer_detected
• ocr_risk

Substrate Evaluation Algorithm#

1. Identify substrate type
   HTML, mobile HTML, PDF, image, OCR, mixed.

2. Detect noise layers
   Ads, AI overlays, commercial prompts.

3. Assess stability
   Based on structure, consistency, and template volatility.

4. Detect layer interference
   Reordering, injected content, translation drift.

5. Evaluate accessibility
   Semantic HTML, alt‑text, heading structure.

6. Compute substrate score
   Weighted by stability and noise.

7. Produce substrate packet
   Structured, RTT‑aligned output.

Examples (Generic)#

Cleveland Clinic#

substrate_type: html
substrate_stability: high
substrate_noise: low
layer_interference: absent
accessibility_stability: high
substrate_score: 0.88

Ping An#

substrate_type: mobile_html
substrate_stability: medium
substrate_noise: high
layer_interference: present
accessibility_stability: low
substrate_score: 0.41

NHS.uk#

substrate_type: html
substrate_stability: very_high
substrate_noise: low
layer_interference: absent
accessibility_stability: very_high
substrate_score: 0.95

Why This Operator Matters#

Medical information is not substrate‑neutral.

Substrate determines:

• how meaning is preserved
• how drift propagates
• how continuity kernels survive
• how AI overlays distort content
• how translation layers alter semantics
• how patients interpret risk

The MEDICAL_SUBSTRATE_OPERATOR ensures that all downstream reasoning is based on clean, stable, substrate‑aware input.

This is the operator that makes the module structurally safe.