HUNT EXECUTION · OUTCOME VALIDATION

THE DECISION DOES NOT END WHEN YOU CLIMB INTO THE STAND

Close the Field Intelligence Loop.

Turn an exact saved HuntScore into a traceable field plan, record what actually happened, and compare the recorded outcome against the saved decision context. One hunt becomes evidence. It never becomes automatic proof that the model is right or wrong.

FIELD VALIDATION READYLoading saved HuntScore and field history…

SAVED HUNTSCOREExact decision snapshot

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FIELD EXECUTIONWhat actually happened

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FIELD VALIDATIONAlignment, limits, compromises

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CONTROLLED LEARNINGNo automatic weight changes

CREATE FIELD PLAN

Start From A Saved HuntScore

Field validation requires a saved HuntScore so the result can be tied to an exact property, stand, hunt date, time window, score, recommendation, risk context, and available provider provenance.

Property

Saved HuntScore Decision

Select a saved HuntScore. A raw weather window or staged camera analysis cannot become a field validation record.

Field validation truth rule: A single sit can support, partially support, contradict, remain inconclusive, or be execution-compromised. It cannot automatically rewrite HuntScore logic.

FIELD HISTORY

Plans + Completed Hunts

No field plans loaded yet.

Planned HuntScore--

Plan Status--

Decision Alignment--

Evidence Strength--

FIELD PLAN

Select a saved HuntScore decision

The exact saved decision context will appear here before the field outcome is recorded.

PROPERTY--

STAND--

PLANNED DATE--

PLANNED WINDOW--

WEATHER PROVENANCE--

STRATEGY CONTEXT--

SAVED RECOMMENDATION --

SAVED RISK

Record The Actual Hunt

Hunter-recorded field evidence

Did You Hunt This Plan?

Actual Hunt Date

Sit Start Time

Sit End Time

Primary Field Result

Total Deer Seen

Bucks Seen

Mature Bucks Seen

Target buck seen Shot opportunity Harvest recorded

First Deer Movement Time

First Mature Buck Time

Did The Wind Hold?

Entry / Access

Human Pressure

Weather materially changed I followed the saved stand/window recommendation

Field Notes

DECISION VALIDATION

VALIDATION STATE

WAITING FOR OUTCOME

--ALIGNMENT

Record the actual hunt to compare the field outcome against the exact saved HuntScore decision.

EVIDENCE STRENGTH--

CONTROLLED LEARNING SIGNAL--

SUPPORTING EVIDENCE

No validation evidence yet.

LIMITS / CONFLICTS

No validation limits yet.

Learning Integrity Rule
A hunt outcome is evidence, not proof. A no-deer sit does not automatically disprove a high HuntScore. A harvest does not automatically prove every part of the model was correct. Wind shifts, contaminated access, major weather changes, or ignoring the saved recommendation are recorded as execution compromises. Field validation never changes HuntScore weights or strategy logic automatically.

Controlled Outcome Learning

Repeated outcomes, not one-hunt conclusions

After multiple field outcomes are validated, BuckVisionAI groups repeated evidence by HuntScore band, stand, hunt window, season, provider provenance, and decision-factor contribution. Learning signals never change the active HuntScore model automatically.

Analyze Repeated Outcomes