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This is less a criticism of the paper than it is a statement of misaligned expectations.

> but the mechanism behind this is entirely hand-waving.

The objective of this paper was not to specify, or even attempt to specify, the mechanism.

> The paper's use of machine learning seems entirely pointless, basically drawing the obvious line between the two sets of points.

Yeah, that is pretty much the entire objective of SVMs.

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> Yeah, that is pretty much the entire objective of SVMs.

Which is hard to do by hand in many dimensions but almost trivial in 2. I haven't read the paper but maybe the OP is complaining about something like that?

Yes, the data is essentially 1-dimensional and looks like "CCC MMMMMMMM". (Seriously, look at Figure 2 graph H in the paper.) It seems entirely gratuitous to use machine learning to build a SVM classifier to separate the C's from the M's, when it's obvious that the C's are on the left and the M's on the right.

Perhaps the use of machine learning helped to acquire funding, or enabled the researchers to acquire skills for future projects.

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