Thanks Jed for the explanations ! 100% agreed on gamut mapping and its importance.
Interesting to observe that the term “gamut compression/mapping” is nowhere to be found on the paper dropbox from the Output Transform VWG. Is this intentional ? 
I double-checked in the aces_rae pdf from 2017 and the term is indeed present (in the D. Artifacts paragraph) :
Gamut compression or mapping based on IPT or ICtCp color spaces would be a fruitful research axes to overcome these issues.
On the other hand, the term “gamut mapping” is mentioned in the Background Information Dropbox paper :
This is a simple, fast gamut mapping algorithm. It maps RGB values onto the 0 to 1 cube using line/plane intersection math which has been optimized to take advantage of the fact that the planes are the [0,1] cube faces. Out-of-gamut points are mapped towards a value on the neutral axis. If the RGB values are linear tristimulus values for arbitrary RGB primaries then the algorithm preserves dominant wavelength on a chromaticity diagram. It also preserves hue in the HSV sense. Light out-of-gamut colors are darkened as they approach the gamut, while dark colors are lightened (i.e. some lightness is traded off to preserve chroma). There are certainly many more sophisticated algorithms for gamut mapping, but this is simple, fast, robust, and useful as a point of comparison.
Maybe it would be nice to see how this algorithm handle our dataset ?
Garrett, at this point, I don’t have anything to add further to the debate. So I’ll just watch Daniele’s video and try to learn something. 
Thanks for your answers and patience !
Update : sorry, this is too interesting ! Minute 16:25 of the video :
Film produces the colours very much in a similar way than nature does it.
Boom, my mind just exploded ! I’ll keep watching !
Regards,
Chris