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CONTROLLED OUTCOME LEARNING · REPEATED EVIDENCE

Repeated field evidence.
Controlled learning.

Turn completed field outcome validations into repeatability signals by HuntScore band, stand, hunt window, season, provider provenance, and decision-factor contribution. One hunt remains evidence—not proof.

PRODUCTION MODEL STATUS LOCKED

Controlled Outcome Learning does not silently alter HuntScore weights, downgrade caps, or Unified Strategy state logic.

01

Build Property Learning Read

Connecting field evidence…
Select a property and analyze completed field outcomes.
FIELD OUTCOMES--Completed hunted plans in the selected evidence window
UNCOMPROMISED--Field sits that can more fairly test the saved decision
DECISIVE VALIDATIONS--Supported, partially supported, or contradicted outcomes
LEARNING SIGNALS--Repeated evidence groups detected
LOCK
LEARNING INTEGRITY RULE

Repeatability before model review.

A harvest does not prove every factor was correct. A blank sit does not prove a high HuntScore was wrong. Compromised wind, access, weather, and recommendation execution are kept visible. Property patterns are learning evidence only.

02

Property Learning Signals

Ranked by review importance and evidence depth
No learning run selected yet.
03

Learning Run History

Fingerprint-reused when the evidence is unchanged
No saved learning runs yet.
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