Calibration

When you say “70% probability,” do things actually happen 70% of the time? This is the track record of your probabilistic predictions — scored with Brier (lower is better) and visualized as a calibration curve.

Total forecasts

5

Resolved

0

Brier score

0.000

(none resolved)

Bias

+0.0%

underconfident

Forecast ledger (5)

NBIS FY2027 revenue >= 9B USD

ai·Resolves 2028-03-15

55%

unresolved

CBRS FY2026 core revenue >= $850M (guide floor)

ai·Resolves 2027-03-15

62%

unresolved

MU FY27 non-GAAP EPS >= $95

hardware·Resolves 2027-10-15

58%

unresolved

CRWV remains FCF-negative through FY27 (no positive annual free cash flow)

ai·Resolves 2028-03-31

65%

unresolved

A second pure-play PIM acquisition by NVIDIA, AMD, or a hyperscaler within 18 months of Qualcomm's UPMEM deal (by 2026-12-31)

hardware·Resolves 2026-12-31T1

30%

unresolved

How calibration works

Every forecast is a probability assignment. When one resolves, it contributes (p − actual)² to the Brier score. Lower is better; perfect prediction is 0.0, coin-flip is 0.25. The calibration curve binning shows whether your 70% forecasts actually resolve true 70% of the time. Record forecasts via scripts/research/forecast.ts, resolve them as outcomes land.

Compare with thesis track record →