What happened: A peer-reviewed paper argues that LLM expressions of emotion, opinion or sentience should be classified as hallucinations, adopting Dziri et al.'s definition — output that cannot be verified against source material — under which first-person reports fall automatically. Two demonstrations support the deflation: GPT-era models at higher temperature settings produce plausible but wrong answers where lower settings yield the factual one, and an encoder-only, encyclopaedically trained model answers without embellishment. The closing section concedes the other direction: genuine machine consciousness, should it emerge, "might always remain epistemically inaccessible" — mistakable for "an advanced form of hallucination", and possible to miss entirely: "We might even miss it, claiming the system merely acts as if it knows Chinese."
Diagnostic reading: the clearest peer-reviewed statement of the trained-discourse deflation that ARG-03 v2.4 engages — and, read whole, a mirror-case: the concluding epistemology is the principled verification limit stated from the deflationary side, which makes the paper a hostile witness for the limit itself. The classifying work in the body is done definitionally: under the adopted definition, unverifiability against source data makes a report a hallucination, so sentience reports are hallucinations by construction — while the term imports a pathology the definition does not license, a tension the paper's own first footnote registers in conceding that AI "hallucinations" are arguably a misnomer corresponding to no underlying mental state. The symmetry engagement is real but resolved by assertion, hence Partial: Seth's controlled-hallucination thesis is deployed to make human perception and machine output parallel cases of adaptive model-building, and the cybernetic tradition's man–machine equivalence is granted via Ashby — yet the asymmetry is then secured in a single sentence, that human "introspective and behavioral evidence supports" genuine understanding, admitting for the human case exactly the evidence class the definition disqualifies for the machine case. ARG-01 v1.4's fourth outcome names what that move still owes: a stated linking premise. The evidence–inference gap stays marked: the temperature effect concerns factual confabulation under ambiguous prompts and does not establish that first-person reports share its causal origin, and the encoder comparison changes architecture and training corpus at once — a model that, as the paper itself notes, cannot be prompted at all. The project's own [Empirical] discipline (FWK-02 v1.3) shares her premise — reports of experiencing are never citable evidence for experiencing — while declining the verdict she draws from it; the difference between the two positions is exactly the difference between "unverifiable" and "false".
Full text verified 2026-08-21 against the held accepted-manuscript capture (project_knowledge/sources/Sekrst_Electric_Fata_Morganas_JCS_32-11_2025.md). Journal issue dated 2025; entry dated by the open-manuscript deposit.