Medical AI benchmarks routinely pair a diagnostic image with the same-visit clinical record, delete the recorded diagnosis, and treat what remains as auxiliary context. The recipe is reasonable. It is not. On 5904 ophthalmic visits across eight cohorts, a frozen text probe still recovers the disease label from the diagnosis-redacted record at 0.944 macro-AUROC, against 0.998 on the unredacted record; the most aggressive dictionary scrub closes less than one further percentage point. The diagnosis is already in the notes.

It is not in one place. A clinical record is written during the diagnostic process, and its fingerprints persist across channels: narrative text alone reaches 0.978, and a view that erases every value and exposes only which fields were populated still reaches 0.854. We introduce CRAFT (Channel-wise Redaction And Floor Test), a portable audit protocol that renders each record into redacted and channel-isolated views and reports each channel’s label recoverability; rankings reproduce under Qwen3.5-9B. Before clinical-text or image-text fusion gains are read as cross-modal reasoning, the text branch’s channel-level shortcut floors must be reported alongside them. https://github.com/yhc98002-bit/The-Diagnosis-Is-Already-in-the-Notes