--- license: cc-by-4.0 pretty_name: cascade held-out eval pool (24h-lagged reveal) tags: - time-series - forecasting - benchmark --- # cascade eval pool — lagged public reveal Daily snapshots of the **held-out evaluation pool** used by the [cascade](https://github.com/TensorLink-AI/cascade) subnet, built from the [tsbench-forge](https://github.com/tensorlink-dev/TSBench-Forge) live catalog of real public time series across the 7 GIFT-Eval domains. **Each snapshot is revealed 24h AFTER it was used for scoring** (`as_of` is a closed UTC day). Because the pool rotates daily, a released snapshot is always for a round that is already scored — it lets anyone **reproduce the leaderboard** without exposing the round currently in play. ## Layout ``` snapshots// one folder per revealed day (as_of) .npy float32, freshest context_length + horizon points metadata.json {series_id: {freq, seasonal_period, domain, source}} provenance.json build config (context_length, horizon, builder_version) ``` Scoring is identity-agnostic: MASE uses `seasonal_period`, CRPS/WQL use the values + a model's quantiles, and the KOTH cluster-bootstrap groups windows by `source`. Re-cut windows of `context_length + horizon`, forecast the horizon, and the metrics reproduce byte-for-byte. ## Latest snapshot — `2026-08-01` - **series:** 3504 - **domains:** transport=2545, energy=367, healthcare=227, nature=193, econ_fin=74, sales=66, web_cloudops=32 - **cadences:** min=2566, D=337, 30min=258, 15min=134, 5min=122, H=53, 10min=15, 6min=10, 240S=6, 15S=1, 10S=1, 1S=1 > This is an **evaluation** set, not training data. Publishing it to train on > would contaminate the benchmark it exists to measure.