A model should be able to tell you when it has stopped being right.

the vocabulary this rests on

Every position above depends on four ideas: admission control, blindness (unknown channel), typed surprise channels and the surprise latent they are decoded from. Hover any of them, or read the full definitions below.

definitions

Glossary

The terms used across the manifesto and how-it-works pages, defined once and cross-referenced.

reference graph

The set of existing models that claimed to cover a question, kept as nodes with declared coverage and validity rather than averaged into one consensus. Every forecaster, simulator or risk engine that made a prediction for the same step becomes a node carrying its own coverage, assumptions and validity conditions. Edges record where two references overlap. Zeno reads the pattern of agreement and disagreement across that graph instead of collapsing it into an ensemble mean, because the shape of who disagrees is the signal.

see also admission control, model-relative surprise

model-relative surprise

Departure measured against what the reference models expected, not against a historical average. The learned object is the difference between reality and the expectations of the models currently in production. The same observation can be unremarkable for one reference set and a severe departure for another; surprise is therefore always relative to a stated set of expectations.

see also surprise latent

surprise latent

A ten-dimensional learned state that encodes the structure of departure — magnitude, persistence, structure, mechanism and coverage. Written z^S_t, the latent is trained under several objectives at once: reconstructing the departure, contrasting regime change, predicting reference validity and an information bottleneck that stops it from memorising the outcome. It is the piece the falsifiable claim is about — that it carries information about future regime change which predictive uncertainty alone does not.

see also typed surprise channels, predictive uncertainty

typed surprise channels

The latent is decoded into separate channels — disagreement, structural departure and blindness — that are never blended into one score. A single risk number cannot tell you whether to act or to look. Typed surprise splits the reading into channels so the response can differ: reference disagreement calls for arbitration between models, structural departure calls for a change of policy, and blindness calls for observation. Each channel carries its own magnitude, timing and consequence estimate in the receiving domain's unit.

see also blindness (unknown channel), information request

blindness (unknown channel)

How much of a low reading is genuine calm and how much is simply not observed. Missing data is treated as a first-class input rather than imputed away. The blindness channel reports the share of the current window that no reference could see — a cloud-covered tile, a halted instrument, a venue that stopped reporting. A quiet surprise score with high blindness is not reassurance; it is an instruction to restore visibility before trusting the reading.

see also information request, typed surprise channels

admission control

A per-reference decision about whether a model still has the right to speak about the current situation. Each reference declares the conditions under which it is valid. Admission control tracks whether the observed regime still sits inside those conditions and marks a reference as admitted, provisional or withdrawn. Withdrawn references keep producing numbers — they just stop being counted as expectation, and the fact of withdrawal is itself reported as evidence that the world moved outside the modelled envelope.

see also model validity, reference graph

model validity

Whether the reference set as a whole is still operating inside its assumptions. An aggregate state — valid, strained or invalid — derived from admission control across references, calibration drift and coverage. It answers the operator's question directly: is the thing I am relying on still right, and if not, since when.

see also admission control

credible tail

An unexpected but constraint-consistent future found by search, not by random sampling. Credible tail search looks for trajectories that are far from reference expectation yet still satisfy domain constraints and the current surprise state. Trajectories that violate a hard constraint are discarded rather than down-weighted, so what survives is a small set of counter-expectations that are hard to dismiss on physical or institutional grounds.

see also typed surprise channels

information request

The model's statement of what should be observed next to resolve the current ambiguity. Rather than only reporting a score, the model names the observation that would most reduce its own uncertainty about whether a departure is real — a re-tasked sensor, a second venue, an instrument check. It is the actionable half of the blindness channel.

see also blindness (unknown channel)

systemic coupling

Explicit edges that carry surprise from one domain into another in the receiving domain's own unit. A departure in Earth Observation may imply exposure in Financial Services or load risk in Critical Infrastructure. Coupling edges declare the mechanism, and propagated surprise is converted into the receiving domain's native unit and attributed back to its source and path. There is no universal risk score.

predictive uncertainty

A model's own stated confidence — the baseline the surprise latent must beat to be worth anything. Variance, entropy or conformal width reported by an existing model. It is the strongest conventional rival: if predictive uncertainty alone were enough to anticipate regime change and model failure, no separate surprise representation would be needed. SurpriseBench runs it as a baseline on identical inputs.

see also surprise latent, lead@FAR

lead@FAR

Average warning time before a break, measured only while the false-alert rate is held at a fixed budget. Lead time is trivial to inflate by alarming constantly, so it is only reported with the alarm threshold locked to a false-positive rate on clean steps (10% in the published harness). A method that cannot hold the budget reports no lead at all.

see also predictive uncertainty