Be sure to contact Open Alex support or Eric from Works Magnet (in the discussion above) to figure out the best approach.
I frequently use works magnet since all of our limited number of works required corrections for the matches (maybe due to ROR ID registration after matching model training or due to issues with generic name elements such as university of applied sciences) .
It may not be the best approach, but I queried your organization in works magnet and I saw that the accuracy of your existing matches seems to be quite high. For this number of works the results pages are not responsive with my device when querying all years or a few years.
To gain insight: these works are likely to have an affiliation string related to your university, but are not matched to it:
The matches for your close partner Maastricht University Medical Center seem to be less accurate.
They are often matched with the ROR ID:
https://ror.org/036pt7h44 'University Medical Center' in Lubbock, Texas, USA as seen in works magnet.
This organization is related to Texas Tech University and Texas Tech University Health Sciences Center.
Not matched for Maastricht University Medical Center:
Possible alternative strings: Maastricht Universitair Medisch Centrum, Maastricht UMC, MUMC.
The Maastricht UMC ROR ID shows 'centre':
https://ror.org/02d9ce178, but since both variants do have correct matches as well this may not be an issue.
In your own interest it could be wise to request a ROR update for this US organization yourselves to prevent future matching issues, but if that organization's generic name is accurate they may not be able to make their name more specific.
Instead OpenAlex would need to adapt their matching algorithm to account for generic name elements like university medical center, or in our case university of applied sciences or they could use country info from affiliation strings to enhance matching.
In our case we were often matched with Avans University of Applied Sciences
In this case the Maastricht University Medical Center is matched with University Medical Center (the Texas Tech University affiliated one).
Those involved (like the ROR team) have stated that affiliation matching is not perfect. Therefore, it is nice to have tools like works magnet, but you could be right that it may not facilitate a very large number of corrections due to manual selection and resolving and page responsiveness.
Even if Works Magnet is not the right approach, try a query to see what it can do and what filters it provides.
If the scale of the problem would not be an issue (due to manual curation, resolving, and page responsiveness) you can query strings for the MUMC and filter on the erroneously matched US organization, then select all works after a brief check and change the ROR match in bulk.
Kind regards,
Koen Bokern, data steward at Aeres University of Applied Sciences.