Need advice for testing of hypotheses related to the self-citation method

[Jorge_Stolfi]

I'm never sure how to determine these priors.

Indeed, that is the weak spot of Bayes's formula.  The result is highly dependent on the prior probabilties, and they are inherently subjective.

How to visualize the meaning of "my probability of VMS being a hoax is less than 0.01%"? Is it like if we had 10000 different manuscripts showing the strange properties of VMS, you'd say only one of them is likely to be a hoax?

OK, you are right, the formula as I wrote is not appropriate for the case of the VMS. I will try to fix it and post it later. 

I would still put my a priori probability of a hoax somewhere close to 10%, that is, about 1 in 10 strange 240 pages long unembellished medieval manuscripts with weird drawings written in an unknown script that have resisted modern attempts of deciphering it for more than a century might be a hoax.

Actually those features make it less likely to be a hoax. Between two paintings dated ~1500, one that that looks like a Leonardo painting, and one that is ugly, weird, badly painted on cheap canvas, and does not look like any other painting ever seen, which one do you think is more likely to have been created with the intent to defraud some rich art collector of the time?

And why do you say "1 in 10"? How many manuscripts similar (in any sense) to the VMS are known, and how many of them turned out to be hoaxes?  Shouldn't it be "0 in 1"? 

I think there is a typo there in your post, should be 0.0001 and 0.9999 in the denominator?

Indeed, thanks. Fixed.

All the best, --jorge