A newly trained model must not deploy unless it meets defined evaluation and risk thresholds. Which approach best fits?

1. Implement a versioned ML pipeline.
2. Use valid step caching keyed to the relevant inputs and implementation.
3. Add an explicit evaluation gate before deployment.
4. Track model versions and promotion state with accountable approval.