As @olibclarke suggested, direct validation can only really come from seeing structural elements that are expected/reasonable, or from carrying on with processing and getting a reasonable gold-standard FSC in refinement.
Repetition (i.e. just clone and run the same job over again) is helpful as well. Other helpful diagnostics are to see if the orientation distribution in ab-initio is reasonable - if you only have one or two populated viewing directions, it’s likely that the ab-initio structure will not be correct (since there just isn’t enough data).
You can also try running ab-initio with multiple classes. You should see that at least one class in this case resolves the same/similar structure to what you got with one class, and the other classes may contain junk particles.
The most reliable way may be to perform tomography and sub-tomogram averaging on your grid. This will provide you not only with a valid initial model, but also show you where your proteins are in the ice. We show a case-study in Figure 9 here: