Pls clarify Out-Of-Sample usage in Demand Management vs Cross Validation

I need to check my understanding about Out-of-Sample Forecasting and Cross Validation.

Usually we leverage in-Sample Forecasting so that we use all history available to produce a Forecast. We can also use History-Off set : According to the user guide : that is a methodology to check Forecast Accuracy by using out-of-sample (This topic explains how you can use the historyoffset for a forecasting profile for performing out-of-sample forecast tuning or back testing)

However we have introduced Cross Validation since 20A and enhanced it in 23C:

In that case, as it is explained, we can enable Cross Validation by using a Forecast Parameter, :