Sanction teardown · E.D. Texas, USA · 2025-09-03
Pete v. Houston Methodist Hospital
What happened
In E.D. Texas, USA, a filing relied on an unnamed/unconfirmed AI tool to help draft legal argument. The court identified the following problems with the citations in that filing:
-
Fabricated (Other)Plaintiff submitted an unsigned affidavit attributed to 'Alexandra J. Smith' (with a Texas bar number) but admitted she never met the person and the State Bar had no record.
-
Fabricated (Case Law)Plaintiff cited 'Taylor v. United States, No. 6:21-cv-448, 2022 WL 257007' which the court could not locate and deemed possibly fake.
-
Misrepresented (Other)Plaintiff asserted service was effected June 10, 2025 and that the clerk entered default June 21, 2025, though the court docket showed no summons or clerk's entry of default.
-
Fabricated (Case Law)Plaintiff cited 'Lee v. United States, No. 1:23-cv-84, 2023 WL 2505510' which the court could not locate and deemed possibly fake.
Which AI tool
an unnamed/unconfirmed AI tool. Note: Charlotin's public database records tool attribution only where a court order, brief, or reporting on the matter states it explicitly; "unidentified" or "implied" means the record indicates AI use but does not name a specific product — we do not guess.
Outcome
Order to show cause
Additional detail
Plaintiff admitted using AI to prepare filings, submitted an unsigned affidavit for a purported attorney and cited cases the court could not locate; court found false statements and potential fake caselaw and ordered show-cause re: Rule 11 sanctions and evidentiary hearing.
How Citation Safe would have caught this
Citation Safe runs three deterministic layers before a brief is filed: (1) does the citation exist against CourtListener's database of published opinions, (2) if quoted, does that exact language appear in the source, (3) does the cited case actually support the proposition it is cited for. Fabricated case citations fail Layer 1. Fabricated or misattributed quotations fail Layer 2 even when the underlying case is real. Misrepresented holdings — a real case cited for a proposition it does not support — are the target of Layer 3. None of these checks involve asking another language model whether the citation looks right; they are lookups and text-matches against the actual source, which is why a hallucinated citation has to survive a direct lookup against the authoritative source — not another model's opinion — to earn a VERIFIED stamp; our measured false-verify rate is published live at /quality.
Check a brief before you file it → · See our live false-verify rate
Source: https://www.damiencharlotin.com/documents/750/Pete_v._Houston_Methodist_Hospital_USA_3_September_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).