Cross-Branch Comparison
cache age 350h 22mFor a single prediction, see its conditional probability across every scenario branch. Predictions whose probability varies widely are "scenario-sensitive" — the position is a leveraged bet on which future fires. Flat rows = robust to scenario uncertainty.
Pick a prediction
High-conviction (≥4) predictions with ≥2 ticker exposures
238_032
End-state of AI is abundance and post-scarce labor — path is 'no firewall'
Labor/Jobs · Alex Wissner-Gross · conv 5/5 · resolves 2029-03
live posterior: 40% (prior 55%)
Scenario range
0.0pp
34% to 34% across 4 scenarios
cache 37 rows · 2026-05-24 04:31 UTC
cf:e20a3cc6aed2
Robotaxi
cumulative — branches can co-occur · range 0.0pp
| Scenario | Scenario prob | P(238_032 | scenario) | Δ live |
|---|---|---|---|
S_ROBOTAXI_TESLA_2026 Tesla FSD unsupervised wide deployment by Nov 2026 | 40% | 34% | -6pp |
S_ROBOTAXI_NATIONWIDE_2028 Robotaxi nationwide expansion by Nov 2028 | 45% | 34% | -6pp |
S_ROBOTAXI_MASS_2030 Robotaxi >10% urban miles by Nov 2030 | 30% | 34% | -6pp |
S_ROBOTAXI_DELAYED Robotaxi mass deployment delayed past 2031 | 20% | 34% | -6pp |
What this tells you
- High sensitivity (≥30pp range): this claim's probability swings wildly depending on which future fires. Sizing should be smaller; pair with a hedge that has the opposite sensitivity profile.
- Flat row (≤10pp range): the claim is robust — same probability in good and bad scenarios. A "no-regret" position; you don't need to time the underlying scenario.
- Spike on one branch: a leveraged thesis on a specific scenario. If that scenario's prior shifts, this position re-rates massively.