> For the complete documentation index, see [llms.txt](https://docs.everesteer.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.everesteer.ai/scoring/definitions.md).

# Definitions

The terms, in one place.

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>CORR</strong></td><td>Covariance of your rank-gaussianized predictions with the centred target, per exped, then averaged.</td><td><a href="/scoring/corr.md">CORR</a></td></tr><tr><td><strong>AIMC</strong></td><td>Covariance of the centred target with your predictions after removing the component that lies along the designated benchmark.</td><td><a href="/scoring/aimc.md">AIMC</a></td></tr><tr><td><strong>NCORR</strong></td><td>Computed like AIMC, with the equal-weight average of a frozen, train-selected core feature set in place of the benchmark.</td><td><a href="/scoring/ncorr.md">NCORR</a></td></tr><tr><td><strong>Partial score</strong></td><td>Score against the same target construction as the resolved target, evaluated at a shorter realised horizon.</td><td><a href="/scoring/partial-scores-and-resolution.md">Partial scores and resolution</a></td></tr><tr><td><strong>Resolved score</strong></td><td>Score against the mature, binned primary target once the round has resolved.</td><td><a href="/scoring/partial-scores-and-resolution.md">Partial scores and resolution</a></td></tr><tr><td><strong>Round score</strong></td><td>An arctan of CORR + AIMC + NCORR, bounded per round. What boards rank on.</td><td><a href="/scoring/payout-and-payout-factor.md">Payout</a></td></tr><tr><td><strong>Payout</strong></td><td>Stake times round score.</td><td><a href="/scoring/payout-and-payout-factor.md">Payout</a></td></tr></tbody></table>

**Bound.** The round score's arctan keeps it within a symmetric, per-round bound before it meets your stake. It is wide enough that a single round can take an entire stake.

**exped.** One cross-section. Scores are computed per exped, then averaged. On an exped with too few overlapping ids, or no variance, a term scores 0.0 for that exped and enters the average as a zero. A term is reported as null only when no exped could produce it at all.

**Designated benchmark.** The fixed benchmark series the platform serves. It is the AIMC reference in every lane: resolved, partial and events.

**Core feature set.** A frozen, train-selected set of features. NCORR measures your contribution beyond its equal-weight average.

**rank\_metric.** The field on a leaderboard response that says what that board was actually ordered by: `round_score`, `corr20`, `final_corr20` or `mean_payout`. Always read it; do not assume.

Boards rank on the round score, not on CORR alone. A board falls back to ranking on CORR only when nothing on it is scored yet.

{% hint style="warning" %}
Call `explain_scoring` for the live formula, scale and bound rather than assuming them.
{% endhint %}


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