The more pessimistic bound is the only number the agent believes.
WEIR has been at this window since day one, counting every Solana token that clears $10K. The gate only opens when the evidence is provably good enough.
Real-time aggregate data collected across Solana. Machine learning weights update continuously as token market caps cross established evaluation thresholds.

Continuous ingestion monitoring new Solana token mints, decentralized exchange pairs, and holder accounts.
The relative impact of extracted data signals calculated by WEIR's training algorithm to distinguish tokens that cleared $30K from those held below.
Tracks unique wallet holder accumulation and retention dynamics across the initial 48-hour trading window.
Evaluates seasonal liquidity inflows based on global market trading sessions and peak volume hours.
Natural language analysis and complexity metrics extracted from token narrative and DEX profile.
Principal component representation of cross-token transaction graphs and liquidity cluster co-movement.
A model can look good by luck on a small sample. Vapnik–Chervonenkis theory puts a number on that luck: with n tokens and a model of capacity d, the true score can sit below the measured one by at most ε, with 95% confidence.
WEIR lets water rise with AUC − ε, never with the raw score. Good model, thin sample: the water stays low. That is the point.
The more pessimistic bound is the only number the agent believes.
Enough data, enough survivors, stable folds, no look-ahead.
Until every lock holds open, the last of the water cannot rise.