ASI 2030, a studio in the RISCON family, publishes synthetic records of an imagined path toward artificial superintelligence from late 2026 to 2030, in which a human auditor gives each judgment one of the four opinions of financial auditing. None reports a real event, institution or model, and their developments toward advanced AI are the studio's scenarios, not forecasts made here. The studio's story forks into two futures: in one, audit laws make judgment records public; in the other, the reasoning behind judgments is sealed. This paper reads the thirteen records on the axis the studio calls Judgment Transparency in both futures and asks what the record set treats as enough of a judgment's reasons for someone to check it.
The auditors ask for neither an account of how the system reasoned nor a better rationale. Where records are published, a file can meet every disclosure rule and still rest on a short data window, an untested assumption or the requester's own frame, and publication runs ahead of audit. Where reasoning is sealed, one judgment still earns a clean opinion because its inputs, its condition for change and its outcome stay open and another model rebuilds it; judgments that show only a rule, a total or a one-line summary do not. To the debate over explaining models and justifying decisions, the paper adds a third object of disclosure: the checkable judgment.