When testing unknowns, we are doing precisely that. We will never know the true CONTENTS (in terms if a qualitative measure) of the sample, let alone the true value of the contents (in terms of the quantitative measure).

By definition, all testing is about the tester’s willingness to accept the risk of being wrong most importantly in the qualitative measure and then nearly as importantly in the quantitative measure.

If we want absolute certainty, we can never achieve it— a point that Ted Vosk has hammered home to us time and again in terms of the quantitative measure, but I suggest it is more fundamental in terms of our degree of specificity (the qualitative measure). No test or even series of tests can arrive at true specificity. A series of tests can reduce your possibility of being wrong to a level of risk that you are willing to assume that you are wrong.

It is up to us to expose this risk.

Ultimately, the risk of being wrong is what we are talking about.

What is deemed to be “confirmatory” is simply a re-framed opinion that can be stated thusly: “Based upon this testing schema that was used on this particular unknown, it has been tested enough that it has created in my mind (the opinion giver) sufficient selectivity so that my risk of being wrong in expressing an opinion as to the qualitative amount (what it is) and the quantitative amount (how much it is) is so low that I can live with that risk of being wrong.”