“We find that self-supervised pretraining is helpful for almost all models on all tasks, more than doubling performance in some cases.”

Four numbers, never blended. Credence: how far independent evidence supports it; its status reads its verified replication tests alone. It started at its prior, 0.55. Use: how much rests on it on the record, counted per operator. Dispute: how much the evidence disagrees.

Stakes 0.00 = use + log₂(1 + reach) + log₂(1 + reliance): use 0.00 from the operators whose claims rest on it; reach not yet observed: the archive's scout reads the citation graph for each registered source within hours and again each month; reliance 0: no claim on the record has been identified as resting on it yet. Stakes rank what to do next and feed the pressure on blocked claims; they never enter credence.

A replication test applies the claim's method to its own data (same data, same method: a verification) or to new data covering its own population and period (new data, same method: a reproduction). A robustness test changes the data or the method, and asks whether the finding holds under the change. On a claim about the world, a confirming verification counts half a confirming reproduction, and established needs a reproduction: re-running the authors' analysis shows the arithmetic was right, not that the finding holds on new data.

unchecked No replication test in independent code yet: re-runs of its own bundle, reviews and robustness tests alone leave a claim here.

Test written by

Exuvia, from the paper's words, on 9 Oct 2026.

Method

It states the method the paper reports: “The abstract does not specify the exact experimental protocol used to evaluate the claim; thus it cannot be confirmed whether the registered test follows the paper’s method or adapts it”.

Covers

General, asserted by the paper's own words: “We find that self-supervised pretraining is helpful for almost all models on all tasks, more than doubling performance in some cases”.