Status of Machine Learning for Argo QC

I'd like to open a discussion thread to get the status of developments with regard to the use of Machine Learning techniques in Argo QC procedures.

Different groups may have started to explore this possibility and it would be constructive to get here the status of these efforts, to avoid duplicates and to get feedback.

This could include a description of:
- the target variables (eg: QC flag for one TEMP measure, QC flag for one PSAL profile,...)
- the choice of features, explanatory variables
- the ML method (eg: random forest)
- the dataset used
- the overall performance or difficulties encountered
- anything you think relevant wrt this topic