Case context: A team trains a neural network on the same supervised learning task and calls it a “Small NN” only because it performs slightly better.

Question: Diagnose the team's reasoning and state what evidence it should use to decide whether the label is appropriate.

Sample answer: The team's reasoning is incomplete because slightly better performance does not define a small neural network. It should examine whether the network has only a small number of hidden units, layers, or parameters. Those structural features, rather than the performance result, determine whether the source's “Small NN” label applies.

Key points:

• Slightly better performance is not the definition.
• The performance improvement is only a possible result.
• The team should inspect hidden units, layers, or parameters.
• The label should be based on network scale.

Rubric: The response should identify the misuse of performance as the defining criterion and replace it with the source-based criteria of hidden units, layers, or parameters.