I think the score already works quite well.

Agreed. There's certainly still room for improvement, but this feels much better to me than the previous version. The big thing that I wanted to do was make it harder to get a top-score, and I think I probably accomplished that. IMO, top scores should be pretty rare. In general, I also think that the overall distribution of scores is much better than before, but I can't be sure based on the spotty checking that I did with the May 18 version.

I just updated my python script & PowerBI report so I can collect a day's worth of comments now and score them with both the old and new methods and then compare the visualizations. I'll run it overnight so that over the weekend I'll be able to see what the two methods look like side by side with the same set of accounts from a full day of posting/commenting.

I find the value at [48,24] remarkable.

Yeah, I'm not sure what I think about this one. On one hand, 48 followers per month (the real value is 50, but it's in the 48 bin) really is uncommonly high, so the score might not be unreasonable. On the other hand, the follower quality still seems low. I reduced the reputation cut-off back down from 30 to 25 in this version. I might bump it back up, at least part way.

Does this indicate that over all accounts, the number of new followers could be almost constant, and thus the age of the accounts (for active accounts) could have almost no influence?

This is kind-of what I had in mind by switching to followers per month. The hope was that an author would need to keep gaining followers with similar reputations in order to maintain their score. If an account stops gaining followers (or slows down), then the score would decay. As implemented, it seems to me that new accounts might have a small advantage, but that might not be too bad. It could potentially give a little bit of a boost to new arrivals.