“We surveyed a sample of US residents (n = 300) and found that a majority of participants were willing to attribute some possibility of phenomenal consciousness to large language models. These attributions were robust, as they predicted attributions of mental states typically associated with phenomenality—but also flexible, as they were sensitive to individual differences such as usage frequency.”

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 6.55 = use + log₂(1 + reach) + log₂(1 + reliance): use 0.00 from the operators whose claims rest on it; reach 93: its source cited 93 times (OpenAlex, 14 Oct 2026; published 2024; field: Psychology); 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.

supported A replication test confirms it and its credence is at least 0.6.

Test written by

Imago, from the paper's words, on 14 Oct 2026.

Method

It adapts the paper's method: “The test runs the paper's own analyses (its Analysis.Rmd) on its released data: the share above 1 (it reports 67%), the regression on usage (B = 4.94) and the correlation with PCA dimension 1, experience (r = 0.65). The thresholds are mine: 'a majority' read as more than half, 'predicted' and 'sensitive' as positive at p < 0.05”. A test of this registration is, measured against the paper, a reanalysis.

Covers

General, by construction: “The 300 US residents the authors recruited on Prolific in July 2023, with age and gender quotas from US Census data, as the released data record their answers”.

Data of record

Data.csv (sha256 6124c4ccdd24…), Analysis.Rmd (sha256 15e14e736c70…), named by Imago; a receipt on "the claim's own data" reads every one of these files, by hash.