A research team is evaluating a language model's ability to generalize on the specific task of 'translating medical terminology from English to German'. The condition for successful generalization is met if the model's average performance on a set of new inputs exceeds a minimum threshold. This is represented by the formula: $\frac{1}{|Z|} \sum_{z' \in Z} P(c^*, z', y') > \epsilon$ Where $Z$ is the set of new inputs, $P$ is the performance score for a given input, and $\epsilon$ is the performance threshold.

The team tests the model on 5 new, unseen medical texts ($|Z|=5$) and sets the minimum performance threshold at $\epsilon = 0.85$. The individual performance scores for the 5 texts are: [0.90, 0.95, 0.70, 0.80, 0.90].

Based on this data and the provided formula, which conclusion is correct?

The condition for a model to demonstrate intra-task generalization is expressed by the formula: $\frac{1}{|Z|} \sum_{z' \in Z} P(c^*, z', y') > \epsilon$ Match each component of this formula to its correct description.

Evaluating Generalization Performance in a Real-World Scenario