If your replicates are not normally distributed, do not choose $normal$.
$Basic$ can give you intervals that are out of the range of your replicated data; e.g. your bootstrapped replicates range between 2-200 but your lower confidence interval is -5.
For $student's$ CI, you need to pass a variance alongside whatever statistics (e.g. mean, median) you are dealing with. I would prefer this over $bca$ if you cannot generate a large number of replicates that can satisfy $bca$. If the number of replicates are small, the $bca$ intervals become unstable. One way of checking the stability is to generate many sets of replicates and identify corresponding confidence limits - most likely you will notice that the range of confidence limits based on $bca$ is wider than the rest.
I don't even know why they have the $percentile$ method, the most confusing of all five.