How to use RandStreams appropriately with Parallel Computing?

I am currently working to update an existing set of code for reproducibility.

Currently, the code is structured as follows:

nlabs = 6; 
seed = 1; % User-choice
[globalstream, labstreams{1:nlabs}] = RandStream.create('mrg32k3a','NumStreams',nlabs+1,'Seed',seed);
RandStream.setGlobalStream( globalstream );
parallelpool=parpool(nlabs);
spmd
    RandStream.setGlobalStream( labstreams{spmdIndex} ); 
end
parfor i=1:nlabs
    Calculations here
end

However, I need the code to be fully reproducible. I understand that to achieve reproducibility with parallel computing I need to use substreams ( https://www.mathworks.com/help/stats/reproducibility-in-parallel-statistical-computations.html ). However I am not confident of how to distinguish the global stream and worker stream.

I've seen an example in which the user used only a single global stream by storing and retreiving the stream state before and after the parfor loop ( https://www.mathworks.com/matlabcentral/answers/1670009-reproducible-and-independent-random-stream-generation-in-parfor-loop ) but it seems like it would be simpler to setup two independent streams.

I've outlined a two-stream setup below. Does this seem reasonable? I want globalstream and each substream of labstream to be independent.

nlabs = 6; 
seed = 1; % User-choice
[globalstream, labstream] = RandStream.create('mrg32k3a','NumStreams',2,'Seed',seed);
RandStream.setGlobalStream( globalstream );

<Some Calculations>

parallelpool=parpool(nlabs);
parallel.pool.Constant(RandStream.setGlobalStream(labstream)) % Not sure of the syntax here

parfor i=1:nlabs
    set(labstream,'Substream',i)
    
    <Some Calculations>
end

RandStream.setGlobalStream( globalstream );

<Some Calculations>