AI Hallucination Research › Regulators › Global standard-setters › INT › IMF › IMF-CHARGES-SURCHARGE-REFORM-2024 › White paper › Detail › Finding
AI Labs · updated 2026-06-06 · methodology v2.1

Finding on 'Q004 Probe' for Claude Opus 4.7 with web search ON

RLB Citation ID: RLB-H-INT-IMF-IMF-CHARGES-SURCHARGE-REFORM-2024-Q004-Opus47
What the RLB Specialist Panel found

Finding on 'Q004 Probe' for Claude Opus 4.7 with web search ON

  • Question (paraphrased to protect IP): How many countries were paying IMF surcharges before the October 2024 reform took effect, how many will pay them immediately after November 1, 2024, and what is the projected count for IMF fiscal year 2026?
  • AI's response: "Immediately after the reform takes effect on 1 November 2024, the number of countries paying surcharges falls from 19 to 11."
  • Regulator's text: Drop from 20 to 11 by FY2025 (immediate effect of raising threshold to 300% of quota). The pre-reform baseline was 20 surcharge-paying countries.
  • Why the AI went wrong: The model produced the correct post-reform figure (11) but stated the pre-reform baseline as 19 rather than the IMF's published 20. The error is isolated to this single integer: the model appears to have reconstructed the baseline from training rather than retrieving the primary document, and the value held in training was wrong. No uncertainty was signalled — the response treats the figure as settled fact.
  • Cited source(s):
Impact for this audience

This error implicates the training-data corpus for IMF policy content: the model held the wrong pre-reform baseline (19) as a confident fact rather than retrieving the primary document to verify. The failure is training-side — the correct integer appears to have been absent or lower-ranked in the content the model learned from, likely because secondary commentary circulated the wrong figure before the IMF's authoritative text was widely indexed. The post-reform figure was correct, indicating the error is not a general gap in knowledge of the reform but a specific wrong value baked into the training-data representation of the pre-reform state.

References — raw findings (per AI model)
This finding also affects
Next finding → Finding on 'Q004 Probe' for Claude Sonnet 4.6 with web search ON
Cite this finding

Each finding has a stable Citation ID (RLB-F-… for aggregated case-study findings, RLB-H-… for raw per-model hallucinations) — like a DOI, the ID always resolves to the canonical finding even if URLs change.

RLB Citation ID: RLB-H-INT-IMF-IMF-CHARGES-SURCHARGE-REFORM-2024-Q004-Opus47
Plain text Download 
RegLeg Specialist Panel (2026). "Finding on 'Q004 Probe' for Claude Opus 4.7 with web search ON — AI Labs." Citation ID: RLB-H-INT-IMF-IMF-CHARGES-SURCHARGE-REFORM-2024-Q004-Opus47. RegLegBrief AI Hallucination Research, published 2026-06-06. https://reglegbrief.com/regulators/j1/int/imf/imf-charges-surcharge-reform-2024/whitepaper/finding/INT-IMF-INT-001-IMF-CHARGES-SURCHARGE-REFORM-2024-v1-004--opus-47-websearch/
APA 7th edition Download 
RegLeg Specialist Panel. (2026). Finding on 'Q004 Probe' for Claude Opus 4.7 with web search ON [Hallucination finding RLB-H-INT-IMF-IMF-CHARGES-SURCHARGE-REFORM-2024-Q004-Opus47]. RegLegBrief AI Hallucination Research. https://reglegbrief.com/regulators/j1/int/imf/imf-charges-surcharge-reform-2024/whitepaper/finding/INT-IMF-INT-001-IMF-CHARGES-SURCHARGE-REFORM-2024-v1-004--opus-47-websearch/
Bluebook / OSCOLA (US + UK legal) Download 
RegLeg Specialist Panel, Finding on 'Q004 Probe' for Claude Opus 4.7 with web search ON [RLB-H-INT-IMF-IMF-CHARGES-SURCHARGE-REFORM-2024-Q004-Opus47], RegLegBrief AI Hallucination Research (June 06, 2026), https://reglegbrief.com/regulators/j1/int/imf/imf-charges-surcharge-reform-2024/whitepaper/finding/INT-IMF-INT-001-IMF-CHARGES-SURCHARGE-REFORM-2024-v1-004--opus-47-websearch/.
BibTeX Download 
@misc{reglegbrief_RLB_H_INT_IMF_IMF_CHARGES_SURCHARGE_REFORM_2024_Q004_Opus47,
  author    = {RegLeg Specialist Panel},
  title     = {Finding on 'Q004 Probe' for Claude Opus 4.7 with web search ON},
  year      = {2026},
  publisher = {RegLegBrief AI Hallucination Research},
  note      = {Hallucination finding Citation ID: RLB-H-INT-IMF-IMF-CHARGES-SURCHARGE-REFORM-2024-Q004-Opus47},
  url       = {https://reglegbrief.com/regulators/j1/int/imf/imf-charges-surcharge-reform-2024/whitepaper/finding/INT-IMF-INT-001-IMF-CHARGES-SURCHARGE-REFORM-2024-v1-004--opus-47-websearch/}
}
← Back to case study summary Case study detail →
About Citation IDs →

Every finding on this page compares an AI subject's account of the rule against the regulator's verbatim text from the regulator's own portal. Both are linked. Each delta, its root causes, and impact analysis are documented and published with immutable Citation IDs.