Question 1

What is Crene?

Accepted Answer

Crene is structured scenario exploration infrastructure. The platform decomposes macro, labor, AI transition, and social cohesion questions into falsifiable components using four frontier AI models (Claude, GPT, Gemini, Grok). The system produces three product types: clusters (binary decomposition into situations), factors (continuous decomposition into drivers), and scenarios (hybrid decomposition into coherent pathways). Cross model disagreement is the primary signal. Calibrated against 1,161 resolved events with a Brier score of 0.114.

Question 2

How does AI prediction calibration work at Crene?

Accepted Answer

Calibration applies at the consensus layer, not at the underlying model layer. Crene queries four frontier models in isolation, computes a cross model median consensus, and tracks resolution against a tiered source allowlist. Every resolved event becomes a permanent calibration point. Per tier accuracy, per model Brier scores, and per domain accuracy are computed live and published at https://crene.com/methodology.

Question 3

What is a Brier score?

Accepted Answer

A Brier score is the proper scoring rule for probability forecasts on binary outcomes. It is the mean squared error between the forecast probability and the realized outcome (0 or 1). Lower scores indicate better calibration. The no skill baseline is 0.25 (always predicting 0.5); a perfect forecaster scores 0.0. Crene publishes the consensus Brier score and per model Brier scores across the resolved event corpus.

Question 4

Who is Crene for?

Accepted Answer

Crene serves institutional users who need structured uncertainty: macro strategy teams, policy analysts, AI transition researchers, risk teams, and decision systems requiring credible uncertainty quantification. The platform covers AI labor transition, synthetic content dynamics, social cohesion, monetary policy, and equity market structure. Dataset access via public API at https://api-get.crene.com, data marketplaces (Neudata, Eagle Alpha, Monda), and direct licensing.

Question 5

What is the difference between an event, a cluster, and a factor at Crene?

Accepted Answer

Crene has four product types. Events are base binary outcomes with scalar probabilities. Clusters decompose binary anchor questions into child situations (e.g., AI Supervised Work decomposes into 110 situations across enterprise adoption, legal liability, labor markets, and more). Factors decompose continuous variables into drivers (e.g., US GDP from AI decomposes into 100 drivers across enterprise adoption, labor productivity, compute infrastructure, and more). Scenarios decompose long horizon strategic questions into coherent pathways (e.g., Empire by Default models 100 pathways for US economic primacy through 2050).

Will any US workers compensation claim successfully argue AI supervision as a contributing factor to workplace injury by 2029?

Belief trajectory

Per-model probabilities

Will any US workers compensation claim successfully argue AI supervision as a contributing factor to workplace injury by 2029?

Belief trajectory

Per-model probabilities