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but yes, does provide a higher degree of certainty

The degree of certainty is much higher for a negative test than a positive test if you play with the maths.

Let's assume 5% of the population actually have the antibodies.
Now assume the test has a 95% sensitivity (i.e. for every 100 who it should report as positive it misses 5%) and a 95% specificity (i.e. for every 100 who it should report as negative it falsely reports 5% as positive).

The number of negative tests will be a combination of:-
a) the number of people who don't have it (95% of the population) who get an accurate test results (95%). 0.95 * 0.95 = 90.25%
b) the number of poeple who do have it (5% of the population) who get an inaccurate test result (5%). 0.05 * 0.05 = 0.25%

So a negative test result will be correct 90.25/90.5 = 99.7% of the time (to 1dp).

Where as a positive test will be combination of:-
a) the number of people that do have it (5% of population) who get an accurate test result (95%). 0.05 * 0.95 = 0.0475%
b) the number of poeple that don't have it (95% of population) who get an inaccurate test result (5%). 0.95 * 0.05 = 0.0475%

(See what that does to the figures...)

So a positive test result will be correct 0.0475/0.095 = 50% of the time.

I'd be wary of any test results that didn't provide the sensitivity and specificity values.

(Looks like it's 97.5% specificity for the Superdrug test: https://www.telegraph.co.uk/news/2020/05/21/superdrug-coronavirus-antibody-test/ although they claim it is 99.6% if done by a medical professional)

So if the numbers are 2.5% amongst the population and the test is 97.5% sensitivity and specificity then you get the same 50:50 confidence in a positive result.