Medicine Module
RTT/1‑Aligned • Zero Drift • Structural • Student‑Safe#
Purpose of This Module#
The Medicine module teaches students how to analyze medical information structurally, using RTT operators to identify:
- substrate stability
- drift sources
- regime differences
- continuity kernels
- patient‑safe synthesis
Students never produce medical advice.
They learn to reason about information, not treatment.
The Three Medical Regimes#
RTT models medical information across three structural regimes:
US — Clinical Regime (Cleveland Clinic‑like)#
- stable html
- low noise
- conservative framing
- explicit escalation logic
China — AI‑Augmented Commercial Regime (Ping An‑like)#
- mobile_html
- high noise
- translation drift
- AI triage overlays
- commercial prompts
- template drift
UK — Public‑Health Regime (NHS‑like)#
- clarity‑first
- standardized escalation rules
- very low drift
- population‑level framing
These regimes are not contradictory — they reflect different structural priorities.
The Six Medical Operators#
The module is built around six RTT operators:
1. MEDICAL_METADATA_OPERATOR#
Identifies substrate, noise, translation layers, AI overlays, commercial layers.
2. MEDICAL_DRIFT_OPERATOR#
Detects template, semantic, translation, AI, commercial, and regime drift.
3. MEDICAL_SUBSTRATE_OPERATOR#
Evaluates substrate stability, interference layers, and accessibility.
4. MEDICAL_REGIME_OPERATOR#
Classifies content into clinical, AI‑augmented, or public‑health regimes.
5. MEDICAL_CONTINUITY_OPERATOR#
Extracts stable symptoms, risks, red flags, actions, and differentials.
6. MEDICAL_SYNTHESIS_OPERATOR#
Produces a drift‑bounded, regime‑aware, patient‑safe synthesis.
Continuity Kernel (Regime‑Invariant)#
Across all regimes, the following elements remain stable:
Stable Symptoms#
- discomfort
- pressure/tightness
- shortness of breath
- fever/systemic symptoms
Stable Risk Factors#
- age
- chronic illness
- hypertension
- diabetes
- smoking
- family history
Stable Red Flags#
- severe chest pain
- difficulty breathing
- fainting
- confusion
- rapid deterioration
Stable Actions#
- emergency escalation for red flags
- follow‑up for persistent symptoms
Stable Differentials#
- cardiac
- pulmonary
- musculoskeletal
- infection
- gastrointestinal
These form the continuity kernel used in synthesis.
What Is Not Stable#
Students must treat the following as drift‑sensitive:
- AI‑generated suggestions
- commercial prompts
- translation artifacts
- template‑dependent ordering
- regime‑specific framing
These are excluded from the continuity kernel.
Student Materials#
- Cheat Sheet —
/student_materials/cheat_sheet.md - Worksheet —
/student_materials/worksheet.md - Printable Worksheet —
/student_materials/worksheet_printable.md - Mini‑Quiz —
/student_materials/mini_quiz.md - Extended Quiz —
/student_materials/extended_quiz.md - Mastery Exam —
/student_materials/mastery_exam.md - Scenario Gauntlet —
/student_materials/scenario_gauntlet.md - Operator Lab —
/labs/operator_lab.md
Instructor Materials#
- Instructor Lab —
/instructor_materials/operator_lab_instructor.md - Scenario Gauntlet (Instructor) —
/instructor_materials/scenario_gauntlet_instructor.md - Rubric —
/instructor_materials/rubric.md - Teacher’s Key —
/instructor_materials/teachers_key.md
RTTcode Operators (Machine‑Readable)#
All six operators have RTTcode signatures in:
/docs/medicine/RTTcode/
These define the machine‑readable contracts for:
- metadata
- drift
- substrate
- regime
- continuity
- synthesis
Module Philosophy#
The Medicine module teaches students to:
- analyze medical information structurally
- identify drift and instability
- understand regime differences
- extract continuity kernels
- produce patient‑safe synthesis
- reason without giving medical advice
This module is part of the TriadicFrameworks system and follows the same standards of:
- zero drift
- operator‑first design
- student accessibility
- AI‑parsable structure