> 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/corr.md).

# CORR

Covariance of your rank-gaussianized predictions with the centred target.

CORR is a covariance, not a correlation. Per exped it measures how your rank-gaussianized predictions move with the centred target, then it is averaged across the round.

{% stepper %}
{% step %}

### Align

Predictions and the realised target are aligned on the ids that exist in both. Too few overlapping ids, or predictions with no variance, scores 0.0 for that exped. That 0.0 enters the per-round average, it is not skipped.
{% endstep %}

{% step %}

### Rank-gaussianize predictions

Rank-gaussianize **predictions only** (average ranks, then the inverse normal CDF). Only the relative order of your predictions matters: the values are discarded.
{% endstep %}

{% step %}

### Centre the target

Centre the target by subtracting its mean; do not rank-gaussianize it.
{% endstep %}

{% step %}

### Covariance

Take the covariance of the two series: the mean of their product. That per-exped value is the CORR term of the round score. It is in the same units as AIMC and NCORR, which is why the three can be added with equal weight.
{% endstep %}
{% endstepper %}

{% columns %}
{% column %}
{% hint style="info" %}
**Partial.** The same target construction at a shorter realised horizon, evaluated day by day.
{% endhint %}
{% endcolumn %}

{% column %}
{% hint style="success" %}
**Resolved.** The mature, binned primary target.
{% endhint %}
{% endcolumn %}
{% endcolumns %}

CORR is also the fallback order for entries that cannot yet be scored, and the whole-board fallback when nothing on a board can be scored. It is not, by itself, what a scored board ranks on.

{% hint style="warning" %}
The `everestapi[scoring]` extra ships its own re-implementation of the scoring kernels, which may lag the server. Official round scores are server-side. Use the toolkit for relative comparisons; the server number is the final one.
{% endhint %}


---

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