MTVF® Module
ISCI™ — Integrity State
Classification Index™
System: MTVF® – Multi-Layer Truth Validation Framework
Category: AI Interpretation Standards
Type: Supervisory Integrity Module
Status: Canonical Module
Version: 1.0
Purpose
ISCI™ provides a standardized method for classifying the structuralintegrity of decisions validated through MTVF®.
Its purpose is to:
- translate validation results into measurable integrity states
- enable consistent classification of validation outcomes
- support supervisory decision control mechanisms
- create traceable integrity reporting
operational.
ISCI™ transforms validation outcomes into clear structural integrity levels.
Minimum Implementation Framework (MIF)
ISCI™ can be implemented using the following minimum classification process.Step 1 — Collect Layer Validation Results
Gather validation outputs from all MTVF® validation layers.Minimum requirement:
- empirical validation result
- consensus validation result
- contextual governance result
Step 2 — Identify Cross-Layer Inconsistencies
Compare layer outputs to determine whether contradictions exist.Document any detected inconsistencies.
Step 3 — Assign Integrity Classification
Based on the detected conflicts, assign the appropriate ISCI™ integrity level.Minimum requirement:
- integrity level assignment
- explanation of classification basis
Step 4 — Record Integrity Report
Generate a structured integrity report containing:
- validation layer outputs
- integrity classification level
- responsible entity
- timestamp
Use Case 1
AI Medical Decision Support SystemsScenario
A hospital uses AI-assisted systems to support diagnostic recommendations.
The system evaluates patient data, medical literature, and treatment protocols.
ISCI™ Application
Validation layers analyze:
- empirical patient data
- consensus signals from medical databases
- contextual clinical guidelines.
Result:
If the system detects structural conflict between empirical evidence and
clinical guidelines, the decision receives a Level 2 classification,
triggering mandatory human review before treatment decisions are made.
Use Case 2
Algorithmic Financial Market MonitoringScenario
A regulatory authority uses automated systems to detect market manipulation.
The system processes large-scale trading data.
ISCI™ Application
Validation layers evaluate:
- empirical trading data patterns
- consensus signals from independent monitoring systems
- contextual regulatory conditions
Result:
If validation layers remain coherent, the decision receives Level 0
classification and enforcement actions can proceed with documented
integrity validation.