Forecasting & calibration
Can a system state a probability that still holds up once the world answers?
Forecasting · Structure · Evidence · Risk
Labs is the research arm behind ARCANE Intel. We test whether machines can read markets honestly: registered before the data arrives, scored in public, and published when the answer is no.
Latest · Evaluation · 17 Sep 2026
Given no fresh evidence, a calibrated multi-model ensemble scored a Brier of 0.284 against 0.212 for the market price at the same moment. The only statistically clear improvement came from walk-forward calibration, which cut Brier by 0.030. This is the floor every later ARCANE forecaster has to beat, published before we try to beat it.
Read the evaluation →Programmes
Can a system state a probability that still holds up once the world answers?
Finding a pattern is cheap. The test is whether a learner can refuse one.
Every claim should carry where it came from and what would break it.
Measure the loss a mandate actually governs, not a convenient proxy for it.
Research record
How Labs publishes
The question, test and refusal conditions are written down before the data can answer.
A score comes with its sample size and a confidence interval, or it is not reported.
A null or a loss is published in the same format as a win, including our own.
Every piece names the observation that would overturn it, the same discipline as every ARCANE article.
Every piece says what it publishes and what it withholds, so the gap is visible rather than hidden.
In preparation
Registered 17 September 2026. Remaining model arms and human judging in progress. Published whatever it shows.
Planned. Held-out enrollment 25 November to 25 December 2026; review no earlier than 25 January 2027.
A reading programme on order, measure and complex systems that generates testable market questions without turning history into a signal.
Every public conclusion remains open to its evidence and its limits.