Cross-Branch Comparison

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For 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
229_001229_002229_007229_011229_012230_013231_013231_021231_026231_041231_050232_017232_018232_019232_055232_060233_007233_016235_012236_030236_033237_025238_018 (selected)238_021238_023238_025238_032238_064239_003239_005
FamilyAllCompute scaleEnergy / gridHumanoid deploymentRobotaxiAGIASI$1T+ IPOMars uncrewedAI pauseRecession
238_018
Uber drivers face rampant, imminent job loss from self-driving cars
Auto/Transport · Dave Blundin · conv 5/5 · resolves 2030-11
live posterior: 48% (prior 65%)
Scenario range
0.0pp
44% to 44% across 3 scenarios
cache 37 rows · 2026-05-24 04:31 UTC
cf:e20a3cc6aed2

ASI

mutually exclusive — exactly one branch fires · range 0.0pp
ScenarioScenario probP(238_018 | scenario)Δ live
S_ASI_FAST_2031
ASI fast: RSI within 5y of AGI
10%
44%
-4pp
S_ASI_MID_2034
ASI mid: Schmidt 'ASI in 6 years'
30%
44%
-4pp
S_ASI_SLOW_2040PLUS
ASI slow: post-2040 / soft takeoff
60%
44%
-4pp

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.