How to programmatically differentiate between extractive and abstractive summarization in NLP?

We are using different pre-trained models in python transformers library, to generate summaries(both extractive and abstractive). So is there a programmatic way, based on the output summary, we can classify it as abstractive or extractive?

One method I think of is using the rouge python library to compute rouge score with respect to original input text(not human reference summary), which will have rouge(specifically LCS) precision score as 1.0 for extractive(since all the words present in summary will be present in original text). Whereas for abstractive summary some words present in summary will not be in original text and hence precision score will be less than 1.0. Please let me know if this is the right approach? Or is there any other way to differentiate between extractive and abstractive summaries?