Does simply counting more models, from 63 to 668, automatically mean this data is useful for research, or is it just more hype?
The idea that raw growth figures translate directly into a "research dataset" feels like saying more students in a class automatically means better learning outcomes, without considering if we have enough chairs or qualified teachers.
What really changes for someone trying to do actual research?
Unless there's a clear process for validation and categorization, like checking if these models are reliable or even accessible, it's just a number, not something you can build solid research on.
For instance, if I'm tracking student attendance, and the number doubles, I still need to know which students, why they're coming, and what they're learning, not just a raw count.