Subjective Bayesians will probably throw up their hands in horror at it, since it would be unphysical to think that the probability of a sample having
any particular calendar age depended on the shape of the calibration curve.
Not exact matches
The distribution for the measurement of carbon - 14
age has (we're assuming) the same standard deviation for every
calendar year, so it's always that case that we get some
particular carbon - 14 measurement that was «unlikely», since any
particular value for the measurement error is unlikely.
You finally filter out from the collection of trials all those with a
particular measured C14
age, and look at the distributions of true
calendar ages that generated it, compared against the measured
calendar age distribution each algorithm output.
You submit a physical sample which has a
particular true
calendar / C14
age combination — a random point on the calibration curve — with some input distribution.
Most of the information in that distribution is from your knowledge of how the
ages of archaeological artefacts are distributed, and in
particular that they are likely to be more uniform in
calendar age than C14
age.