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Squeeze setup state

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Squeeze setup state

What it is

Squeeze setup state — registry key squeeze_setup_state.

Companion column to squeeze_setup_score; carries the state label / active-trigger list (see app/signals/squeeze.py).

Data-pyramid tier

T3 — Lens. This metric sits at the lens layer of the platform’s six-tier data pyramid (T0 raw inputs → T5 actionable read). The tier reflects how far the value is from a raw measurement — not how strongly it is validated. Abstraction and validation are separate axes: a higher tier is not a claim of stronger evidence.

Horizon & validation

No validated skill horizon is on file for this metric — read it as context / a data carrier, not a validated edge. Stamps are added only when a gated research verdict lands.

Source

Source module: capture
Data source: computed

Derived metric — produced inside the platform (app/signals/capture.py or equivalent) rather than fetched as a raw upstream value. See the How it's computed section below for the formula.

How it’s computed

Categorical state from squeeze_setup_score: ‘primed’ (≥3 triggers) / ‘partial’ (2 triggers) / ‘none’ (0–1 triggers) — or ‘insufficient_data’ (BS2 abstain) when fewer than _MIN_AVAILABLE (3) of the 4 inputs were derivable, so a thin input set can’t fake an all-clear ‘none’. See app/signals/squeeze.py:PRIMED_THRESHOLD.

Where it surfaces

Health-score / alignment role

Data carrier — no implication, no health-score contribution.

Persisted for downstream consumers (sparklines, base-rate matcher, calibration substrate) but does not classify into BULLISH / NEUTRAL / BEARISH and does not contribute to the 0-100 health score.

Release cadence

See also