INPUT LEDGER
What is known, entered, or assumed.
| Input | Value | Origin |
|---|---|---|
| Weights | Stocking 35; habitat 25; access 15; weather 15; distance 10 | Illustrative model |
| Candidate scores | 80, 72, unknown, 90, 60 | Illustrative normalized inputs |
| Missing component | Access | No reliable public evidence |
| Unknown policy | Reweight known components | Declared model rule |
REPRODUCIBLE CALCULATION
Follow the intermediate result.
Known weighted sum
Formula or rule: 80×35 + 72×25 + 90×15 + 60×10
Result: 6,550 weighted points
Known weight
Formula or rule: 35 + 25 + 15 + 10
Result: 85
Reweighted score
Formula or rule: 6,550 ÷ 85
Result: 77.1 / 100
Confidence label
Formula or rule: One decision layer missing
Result: Score shown with access unknown
DECISION READING
What the result means.
Assigning zero would falsely claim poor access; assigning a neutral value would invent evidence. Reweighting preserves the known comparison while a separate confidence label exposes the missing layer.
SENSITIVITY
What could change the answer.
- If access is a mandatory safety gate, the candidate can be withheld instead of merely reweighted.
- More missing layers should lower confidence even if the normalized score stays high.
- Weights should be visible because changing them can reorder candidates.
BOUNDARIES
What this case does not prove.
- The weights and component scores are illustrative, not a live recommendation.
- A high score does not establish legal public access.
- Unknown data must be verified with the responsible land or wildlife agency.
OFFICIAL SOURCES
Where factual context is verified.
RELATED FINVECTOR CASES
Change one assumption and compare again.
Each case keeps inputs, arithmetic, evidence, and uncertainty in separate layers.