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
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.

Crene Factors | Continuous State Variables for AI Transition