I think I understand your criticism. There is no inherent ground truth in the image. The mass example is great since a 2D plane can't capture the quantity mass it's literally impossible the dimensions don't work. At best a 2D plane could show you correlations of mass (mass vs something plotted out). Hence this is just modern AI aka pattern-matching on steroids.

I think a counter argument would be that if there is SOME signal in the photos AND there's enough training data that does have the correct ground truth signal that the scientists are matching up then you can have SOME level of accuracy. If the training set can reasonably cover the space of possibility that we're interested in then we can get reasonable interpretations.

However in this case the insane number of physical phenomena will always be larger than any training set so this approach should NEVER generalize there will always be way too much noise which is what the scientists have figured out here. So I agree with you that it's extremely limited but I don't think I'd call it pseudoscience there might be very limited domains where for example the only data we have available are images and so such a tool may be appropriate.

I definitely share your frustration though since any half way decent scientist should have just done a thought experiment instead and figured that this wouldn't work well. This smells like BS academic marketing where they always inflate their own impact and significance.