Sanction teardown · US Tax Court, USA · 2026-02-09
Peter L. Clinco v. Commissioner
What happened
In US Tax Court, 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:
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Fabricated (Case Law)Counsel cited "Cacchillo v. Commissioner, 130 T.C. 132 (2008)" in support of a signature requirement; the Court found no such case at that citation and that the citation appears fabricated.
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Misrepresented (Case Law)Counsel cited "Miller v. Commissioner, 57 T.C. 440 (1971)" to support a proposition about notices of deficiency; the Court observed the actual Miller decision cited by counsel is a T.C. Memo. (1984-448) and the reporter page at 57 T.C. 440 is a different case, so the citation was incorrect/misrepresented and did not support counsel's point.
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Fabricated (Case Law)Counsel cited "Tefel v. Commissioner, 118 T.C. 324 (2002)" for a signature-formalities proposition; the Court found no case named Tefel at that citation (page 324 of 118 T.C. is Hillman v. Commissioner) and treated the citation as fabricated.
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
Admonishment
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.
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Source: https://www.damiencharlotin.com/documents/1474/Clinco_v._Commissionner.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).