Crene Factors — continuous probabilistic distributions
Examples · Factor maps
Continuous distributions.
A factor is a continuous state variable forecast as a cross-model percentile distribution. Each factor decomposes into roughly 100 drivers that explain movement in the distribution.
How to read factor maps
Use factor maps when the question is a level, range, or distribution rather than a yes-or-no thesis.
p50
Current ensemble estimate
p5 to p95
Outer uncertainty band
Model spread
Where models disagree
Drivers
Variables that could move the range
Active factor maps
Loading factors…
Each factor carries a quintile distribution (p5, p25, p50, p75, p95) aggregated across four frontier models, with cross-model disagreement and a derived confidence label. Drivers explain how the distribution moves, not how it is generated. Forward-looking calibration is tracked alongside binary thesis map calibration on the methodology page once horizon resolutions accrue.