The test was whether producing equivalent accuracy and detail for summaries of all books in its training corpus was a feature of ChatGPT's ability to natively g

The test was whether producing equivalent accuracy and detail for summaries of all books in its training corpus was a feature of ChatGPT's ability to natively generate them from standalone source material or whether Silverman's detailed summary was likely just a "summary of summaries", not whether ChatGPT produced a result at all. From the comment you reference, it failed the test because the result was hallucinated. You can pick something else that's in the training set that has SparkNotes and many popular reviews to compare. I routinely feed novel data sources into LLMs to test massive context and memory, and none produce anything similar in quality to what is being exhibited.