---
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a newer snapshot has superseded it, so no revealed pool can be selected by a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 — `2026-07-28` (block 8719200)

- **series:** 2896
- **sha256:** `bf5258612d7d9be71764a65caa2966ac114a4f559baad7082171af6025b1ad66`

> This is an **evaluation** set, not training data. Publishing it to train on
> would contaminate the benchmark it exists to measure.