Converting intentionally underexposed images

How do I make the conversion reflect an intentionally underexposed image. I realize that the software looks for the white and black points. The black point can be verified because it tonally matches the film edge. But it assigns the white point to the brightest object in the frame. What if I want my tonal range to be between 0-40%? In other words, what if I made a portrait against black and exposed for the skin to be a stop under?

I’ve experimented with bringing the White Clip down. This gets me to where I want tonally because it widens the latitude of the default conversion, but skews the color balance considerably.

When the tonal range of the negative is spread out, I’ve been successful doing the majority of the work in NLP and then finishing with a TIFF. But I’m trying to figure out a solution in NLP for the examples above (narrow, underexposed tonal range) that doesn’t require such a drastic correction with an intermediate.

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