agreed, looks like good training and should be capable to pick more rares and bolster the dataset with “hidden” particles that were in your data but difficult to pick/identify. to alleviate your original problem of over-representation.
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On a different note - you might consider using rebalance orientations (& perhaps BLUSH regularization in relion) as described here: x.com
I have tried iterating single class ab initio & rebalance orientations (discarding paricles with worst alignments3d/error), and in some cases have seen substantial improvement in the quality (isotropy) of the initial model.
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