certainty · epistemic
a model whose predicted range is narrow
Examples
- The Hubble Space Telescope's gyroscopes failed repeatedly, requiring five servicing missions to maintain precise pointing. engineering
- The Federal Reserve raised interest rates seventeen times between 2022 and 2023 to narrow inflation forecasts. economics
- GPS satellites correct their orbital ephemerides every two hours to keep positional predictions within one meter. computing
Emergence
through: A model with a spatially narrow range confines predictions tightly, reducing allowable variation in outcomes.
- tight prediction bounds
- low parametric drift
- focused expectation
Chain to foundations
as tree
- certaintyL10
- modelL9
- patternL0
- likeL3
- actL3
- saysL8
- messageL7
- informationL6
- differenceL1 (shown above)
- marksL5
- differenceL1 (shown above)
- partL1
- changeL1 (shown above)
- patternL0 (shown above)
- surfaceL4
- boundaryL2
- spaceL0 (shown above)
- differenceL1 (shown above)
- changeL1 (shown above)
- touchL3
- spaceL0 (shown above)
- boundaryL2 (shown above)
- interactionL2 (shown above)
- changeL1 (shown above)
- partL1 (shown above)
- boundaryL2
- patternL0 (shown above)
- entitiesL4
- othersL2 (shown above)
- boundaryL2 (shown above)
- distinctL3
- differenceL1 (shown above)
- othersL2 (shown above)
- spaceL0 (shown above)
- putL3
- informationL6
- othersL2 (shown above)
- distinctL3 (shown above)
- entitiesL4 (shown above)
- getL5
- makeL4 (shown above)
- messageL7
- windowL7
- parameterL4
- rangeL3
- boundaryL2 (shown above)
- persistL1 (shown above)
- changeL1 (shown above)
- outsideL6
- partL1 (shown above)
- narrowL5
- rangeL3 (shown above)
- modelL9
Neighborhood
Concepts that depend on this one above; what it is built from below.
Relations
| contrasts-with | risk.uncertainty | while risk involves a wide window of possible outcomes, certainty involves a narrow one |
| contrasts-with | drift.aimless | a narrow window reduces space for drift, though drift may still occur |
| enables | maintenance.upkeep | narrow windows require less maintenance when parameters stay within expected bounds |
| abstracts | feedback.communication | a narrow model may be shaped by tight feedback loops |