Manipulating Hierarchical Clustering (DistMatrix) results

The target is to classify binary flags (100+ pcs) in data entries, in order to create clusters of the flags, and in this way classify the data entries. Now, I manually programmed logic to write a Distance Matrix, and used the Hierarchical Clustering (DistMatrix) node to classify them. Unfortunately, the output format is a strange data type called DistanceVectorDataCell, which is accepted only by a viewer node and the Model Writer. This is supposed to be a collection of DoubleCells, but no node can split them. The Model Writer writes binary-format FILE files. How can I extract the hierarchical tree? First of all, it's way too large to be conveniently viewed in KNIME's viewer. Second, I want to manually prune and process it using regular KNIME logic. I know already from the nature of the data that many of the classifications will be spurious or misleading, and need to be converted by hand into an actually useful classification, which will then be again reused in another context.

For Distance Matrix, the format is readable by Split Collection Column, and can be written with CSV writer then read by Distance Matrix Reader. Are there similar nodes for Model? In development? Currently the only method I have is to manually copy the results from the viewer, which is probably not what the developers intended.

I could try the Hierarchical Clustering node, but the data is binary and categorical, so the distances from e.g. flag 14 to flag 15 or flag 103 are meaningless, and the Euclidean distances make no sense. Currently I use Tanimoto distances with some multidimensional reprocessing. The issue with the data is indeed this: the flags are largely meaningless even by themselves, and need to be classified into a smaller set of hierarchical nodes, before they can be used to classify the data in a manner than makes sense to a human reader. I could do this by hand, but for this, the number of flags is rather large, and it risks inconsistency.