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Paper Citation Record · LEDGER

A Shared Standard for Valid Measurement of Generative AI Systems' Capabilities, Risks, and Impacts

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.01934.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.01934 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T03:40:25.093487Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-22T03:41:00.097378Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 20920e93-0cab-456f-8dd1-3171ea9fd02d · inbound

Making AI Evaluation Deployment Relevant Through Context Specification cites this paper.

Making AI Evaluation Deployment Relevant Through Context Specification A Shared Standard for Valid Measurement of Generative AI Systems' Capabilities, Risks, and Impacts

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:50:05.150614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T14:46:09.944168Z digest=sha256:c82333b7e3174423b22f0a491f973b91a82b0764c365850214706c2df72a26da

Observation e3dcc03d-55a4-40c1-9081-293036925e15 · inbound

Healthcare LLM Benchmarks Are Only as Good as Their Explicit Assumptions cites this paper.

Healthcare LLM Benchmarks Are Only as Good as Their Explicit Assumptions A Shared Standard for Valid Measurement of Generative AI Systems' Capabilities, Risks, and Impacts

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-22T03:41:00.101171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-22T03:40:25.093487Z digest=sha256:7a57c5c87e05d2d4d81142b1de51cca1f2d8f67f7995762cfcfd543aef851c7a