MEDICAL_REGIME_OPERATOR

RTT Operator — Medicine Module#

Classifying Medical Information by Regime Logic#

Purpose#

The MEDICAL_REGIME_OPERATOR identifies the medical regime governing a piece of medical information.
A regime is not a country — it is a structural logic:

• how symptoms are framed
• how risk is communicated
• how treatment is prioritized
• how uncertainty is handled
• how escalation is defined
• how the patient is positioned

This operator determines whether the content follows:

• clinical regime (US / Cleveland Clinic)
• AI‑augmented commercial regime (China / Ping An)
• public‑health regime (UK / NHS)

This classification is essential for continuity, drift, and synthesis.

What This Operator Detects#

1. Regime Logic#

Each regime has a distinct structural fingerprint:

Clinical Regime (US — Cleveland Clinic)#

• conservative framing
• physician‑centric
• symptom → cause → treatment
• low drift
• high continuity
• risk escalation is explicit

AI‑Augmented Commercial Regime (China — Ping An)#

• AI triage overlays
• dynamic symptom mapping
• commercial prompts
• mobile‑first structure
• translation drift
• high template volatility

Public‑Health Regime (UK — NHS)#

• clarity‑first
• population‑level framing
• escalation thresholds are standardized
• extremely low drift
• minimal commercial influence

2. Regime Signals#

The operator identifies regime signals such as:

• clinical anchors (US)
• AI‑generated suggestions (China)
• public‑health escalation rules (UK)
• commercial overlays (China)
• risk‑first framing (US)
• symptom‑first framing (China)
• action‑first framing (UK)

3. Regime Drift#

Some content shifts regime over time:

• Ping An pages may shift from human‑written → AI‑augmented
• Cleveland Clinic may update clinical guidelines
• NHS may update public‑health recommendations

The operator flags:

• regime_shift_detected
• regime_stable

4. Regime Coherence#

Coherence measures how consistently the regime logic is applied:

• section ordering
• risk framing
• escalation logic
• treatment hierarchy
• uncertainty handling

Coherence levels:

• high
• medium
• low

Inputs#

The operator accepts:

• raw medical pages
• multi‑snapshot versions
• multilingual content
• AI‑generated triage outputs
• metadata packets
• substrate packets
• drift maps

Outputs#

1. Regime Classification Packet#

{
  "regime": "ai_augmented_regime",
  "regime_coherence": "medium",
  "regime_shift": "regime_shift_detected",
  "regime_signals": [
    "ai_generated_content_present",
    "commercial_overlay_present",
    "mobile_first_structure"
  ]
}

2. Regime Score (0–1)#

3. Regime Flags#

• clinical_regime_detected
• ai_augmented_regime_detected
• public_health_regime_detected
• regime_shift_detected
• regime_incoherent

Regime Classification Algorithm#

1. Ingest metadata packet
   Substrate, drift, translation stability.

2. Identify regime signals
   Clinical anchors, AI overlays, public‑health framing.

3. Evaluate framing logic
   Symptom‑first, risk‑first, action‑first.

4. Detect commercial influence
   Upsells, telemedicine prompts.

5. Detect AI augmentation
   Dynamic triage, probabilistic scoring.

6. Assess regime coherence
   Consistency across sections.

7. Detect regime drift
   Compare across snapshots.

8. Produce regime packet
   Structured, RTT‑aligned output.

Examples (Generic)#

Cleveland Clinic#

regime: clinical_regime
regime_coherence: high
regime_shift: none
regime_signals: ["clinical_anchors_present"]
regime_score: 0.91

Ping An#

regime: ai_augmented_regime
regime_coherence: medium
regime_shift: regime_shift_detected
regime_signals: [
  "ai_generated_content_present",
  "commercial_overlay_present",
  "mobile_first_structure"
]
regime_score: 0.47

NHS.uk#

regime: public_health_regime
regime_coherence: very_high
regime_shift: none
regime_signals: ["public_health_escalation_rules"]
regime_score: 0.96

Why This Operator Matters#

Medical information is not neutral — it is regime‑shaped.

This operator reveals:

• why Cleveland Clinic feels conservative
• why Ping An feels dynamic and commercial
• why NHS feels clear and standardized
• why advice differs across countries
• why drift behaves differently across regimes

It gives the module the ability to say:

“This isn’t contradictory — it’s regime‑specific.”

This is the operator that makes the module intelligent.