Open science is often discussed as a release strategy: publish the code, share the dataset, post the model card. That is necessary, but incomplete. A research ecosystem also needs to know what was tried and did not work, especially when those attempts were plausible enough that another team might repeat them.
Negative results are expensive to ignore. In health AI, repeated dead ends do more than waste compute. They slow validation, distort expectations, and hide assumptions that matter for safety and equity.
What counts as a negative result
A negative result is not a careless experiment or an underpowered test. It is a well-specified attempt whose outcome changes what the field should believe. Sometimes a modality adds no meaningful signal. Sometimes a model performs well overall but fails in a subgroup. Sometimes a benchmark is too leaky to be trusted. Sometimes the simplest baseline wins.
Each of those outcomes is useful if documented clearly. The point is not to celebrate failure. The point is to convert failed expectations into shared knowledge.
How we document them
Cytognosis plans to attach negative findings to the same release system as positive findings: versioned notes, methods, cohort context, evaluation boundaries, and a short explanation of what changed in the roadmap because of the result.
- Was the input data insufficient, biased, or too noisy?
- Did the model fail generally, or only in a specific cohort?
- Was the hypothesis wrong, or was the measurement strategy inadequate?
- Should the result block release, narrow the claim, or create a new benchmark?
Why this matters for trust
Health AI has an incentive problem. The most shareable story is usually the strongest result. But the most useful story for a research community is often the full distribution of results: where the system worked, where it failed, and where it remained ambiguous.
Publishing negative results is one way to keep the work honest. It turns uncertainty into something the community can inspect rather than something hidden behind the next announcement.