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Measurement layer
The data layer measures the evidence behind living decision records.

Use this page to inspect the resolved corpus, calibration record, model forecasts, and named resolution sources behind Crene's decision record system.

Review a thesisView methodology

Crene Data: Calibration Corpus

Measurement layer · Public record

The evidence and measurement layer behind Crene decision records.

Events, thesis records, factors, and scenarios form the public evidence and measurement layer behind Crene decision records. Binary events preserve independent model reads, named resolution sources, and Brier scores after resolution. Collection pages distinguish live records from frozen states and archived scenario records, while factor records remain active continuous distributions.
Read the methodology →
…active binary forecasts

Across all categories. Repolled daily.

…resolved questions

Closed against named sources. Binary outcomes are Brier scored.

…broad corpus Brier

Lower is better. Broad resolved corpus, rounded. See methodology for leakage-controlled and macro-only subsets.

…directional accuracy

Consensus direction vs outcome.

Assumption structure

Raw count tells you coverage. Structure tells you whether that coverage is actually diversified.

Crene separates the number of questions from the independence of the assumptions underneath them. A scenario, factor, or cluster can track many components while still depending on a small number of shared drivers. Question density across domains is the first read on that structure. As the observation record deepens, Crene estimates how many effectively independent assumptions sit underneath each object.

Question density is a structural read, not a correlation estimate. It shows how tightly each object's questions cluster by domain. Crene does not publish exact effective-independence or covariance figures until the observation record is deep enough to estimate them reliably. The same rule applies here as everywhere else on the page: no number is promoted before the record can support it.

Corpus reconciliation

The data page uses the broad corpus view. Total resolved questions refers to the full Crene-native resolved set currently in the database. The headline broad corpus Brier is rounded and differs from the leakage-controlled benchmark and macro-only subset discussed on the methodology page. Model leaderboard sample sizes are per-model rows, so they may differ from the consensus benchmark.

What is in the corpus
Multi model forecasts

Independent probability estimates from four production models (Claude, GPT, Gemini, Grok) for binary forecast objects. No model sees another model output.

Events

Binary outcome questions across macro releases (CPI, NFP, PMI), central bank decisions, commodities, crypto, policy, and market events. Each resolved against a named source.

Thesis Maps

One live Warsh map and two frozen AI records decompose yes or no investment views into assumptions. Each record distinguishes current model reads from immutable weekly freezes.

Factor Maps

Three active continuous distributions track the S&P 500, US 10Y Treasury yield, and US GDP attributable to AI, with recent movement, uncertainty, model disagreement, and driver review context.

Scenario Records

Four archived scenario records preserve 400 authored pathways across AI labor, US primacy, European rearmament, and India growth. Pathway counts describe authored coverage, not probability.

Belief trajectories

Consensus probability is snapshotted daily for binary forecast objects. The full evolution of the forecast is preserved through resolution.

Per event Brier scoring

Each model is scored on resolved binary events. Per model performance is measured continuously, not curated. Continuous factors and long-horizon scenario structures require different calibration metrics as outcomes accrue.

Continuously growing

New investment thesis maps, factors, and scenario components expand the corpus alongside macro, policy, market, and AI-related event flow. Resolutions compound the calibration signal.

How resolution works

Every outcome is tied to a verifiable source. Crene resolves binary events against a tiered source allowlist. Resolution is automated, but the source for each outcome is named and auditable.

Tier A
Primary

Government statistical agencies, central banks, regulators. SEC filings, BLS releases, Fed statements, BEA, BoJ, ECB.

Tier B
Authoritative secondary

Major news wires reporting primary releases. Reuters, Bloomberg, AP, agency wire confirmations.

Tier C
Corroborating

Used only to confirm Tier A or B. No event resolves on a single Tier C source.

Why this matters

Events, thesis records, factors, and scenarios form the evidence layer behind Crene's decision record system. Four model surfaces feed one resolved-event calibration record. Structural representations remain separate from scored evidence until outcomes accrue.

Access
Download Sample CSVView JSON

Data access. Resolved event archive, per-event 4-model breakdown, calibration history, and thesis record structure behind the private thesis review workflow. Use the form below.

Marketplaces. Crene is listed on Neudata, Eagle Alpha, and Monda for institutional procurement.

API. Programmatic access to the public evidence and measurement layer behind live and resolved Crene records. API documentation.