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license: cc-by-4.0
pretty_name: cascade held-out eval pool (lagged exact reveal)
tags:
- time-series
- forecasting
- benchmark
---
# cascade eval pool — lagged public reveal (exact bytes)
Retired snapshots of the **held-out evaluation pool** used by the
[cascade](https://github.com/TensorLink-AI/cascade) subnet. Each folder is a
**byte-identical mirror of the `pool/snapshots/block-<N>.tar` that validators
scored** — downloaded from the private pool bucket, sha256-verified against the
publisher index, and republished unmodified. A snapshot is revealed only after
a newer snapshot has superseded it, so no revealed pool can be selected by a
current or future round.
## Verifying a round receipt
1. Your receipt's pool provenance carries the snapshot tar's sha256.
2. Find the folder whose `POOL_SHA256` matches; `block-<N>.tar` in that folder
is the exact artifact — hash it yourself to confirm.
3. Series order = filenames sorted lexicographically; `window_ids` are
positional (`w<i>` = the i-th series in that order).
## Layout
```
snapshots/<as_of>-block-<N>/ one folder per revealed snapshot
block-<N>.tar the EXACT tar validators scored
POOL_SHA256 its sha256 (matches receipts + publisher index)
<series_id>.npy the same files, unpacked for convenience
metadata.json {series_id: {freq, seasonal_period, domain, source}}
provenance.json build config recorded at publish time
```
Legacy `snapshots/<YYYY-MM-DD>/` folders (through 2026-08-03) predate this
scheme: they were **rebuilds**, not byte mirrors, and are known to differ from
the scored tars (see the repo issue history). Use the `-block-<N>` folders for
exact replay.
## Latest revealed — `2026-08-05` (block 8776800)
- **series:** 1101
- **sha256:** `c6340ab7a04619438f214de69468f0b5f13359ec5b9e9034ef50f279be5a1fcb`
> This is an **evaluation** set, not training data. Publishing it to train on
> would contaminate the benchmark it exists to measure.
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