Submissions are evaluated using the **Weighted F1-Score** between the predicted and actual labels.

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The F1-Score is the harmonic mean of precision and recall, effectively balancing both false positives and false negatives.

$$
F1 = 2 \times \frac{(\text{Precision} \times \text{Recall})}{(\text{Precision} + \text{Recall})}
$$