A time-series forecasting model is evaluated using random splits that place future observations in training and earlier ones in validation. Which approach best fits?

1. Minimize unnecessary sensitive inputs and enforce approved data access.
2. Maintain model, dataset, and training-code provenance.
3. Use time-aware splits that respect prediction chronology.
4. Define labeling guidelines and measure and resolve annotation disagreements.