Document Type: Structure
Status: Active Structure
Version: v1.0
Authority: Research Brain
Parent: Research Brain Architecture
Applies To: Reusable research observations across multiple opportunities
Linked Systems:
Research Intelligence Database
Opportunity Pattern Library
Affiliate Brain Pattern Recognition
MWMS Signal Intelligence Architecture
Purpose
Defines how Research Brain stores reusable signals observed across multiple research tasks.
Signals allow MWMS to detect:
repeated structural patterns
emerging positioning patterns
recurring funnel structures
repeated promise structures
recurring risk signals
Signals allow intelligence to accumulate across time.
Signal Definition
A signal is a recurring structural observation appearing across multiple research contexts.
Examples:
common angle structures
recurring funnel types
repeated pricing patterns
recurring risk patterns
repeated positioning themes
Signals do not imply performance.
Signals describe pattern visibility.
Signal Logging Categories
Signals may be logged in categories such as:
Angle signals
Funnel signals
Offer model signals
Market structure signals
Risk signals
Proof structure signals
Signal classification improves reuse potential.
Signal Use Rule
Signals support:
pattern awareness
structural familiarity
research efficiency improvement
Signals must not become assumptions.
Signals must not override observation.
Signals must not simulate predictive certainty.
Relationship to Affiliate Brain
Signals may help Affiliate Brain identify recurring structural environments across testing opportunities.
Signal awareness supports pattern recognition.
Testing still determines behavioural outcomes.
Architectural Intent
Signal logging allows Research Brain intelligence to improve without distorting evidence discipline.
Signals support structured pattern awareness across MWMS.
Change Log entry
2026-03-26 — Added Research Signal Logging Structure v1.0
Defines structured logging approach for reusable research signals across MWMS research tasks.