Transparency is more important than accuracy.

The problem with many scoring systems has never been about "how accurate they are,"
but rather that you have no idea how they arrive at their conclusions.
Once a black box exists, trust can only rely on endorsement, not understanding.

@bluwhaleai's Whale Score takes a different approach.
It doesn't give you an isolated score, but breaks down the score into components:
the contributing dimensions are there, the historical changes are there, and the percentile ranking is also there.

You may not agree with its weighting design,
you may question whether a certain metric is overestimated,
but at least you understand:
what it is looking at, what it is ignoring, and what it is biased towards.

This kind of "debateability" itself is the foundation of trust.
It's not about everyone agreeing, but about allowing different judgments to be based on the same visible facts.

In on-chain finance,
transparency is not an add-on,
but a prerequisite for establishing trust.

Bluwhale moves the scoring from "authoritative conclusion"
back to "understandable judgment process."
This step may be more important than tuning the model by another 5%.