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Paper Citation Record · LEDGER

Does AI help humans make better decisions? A statistical evaluation framework for experimental and observational studies

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.12108.

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

pith.paper-citation-record.v1
2403.12108 v3

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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:02:21.153493Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b6e81816-b8a1-439f-b53f-0fe6cf12ec67 · inbound

Partial identification via conditional linear programs: estimation and policy learning cites this paper.

Partial identification via conditional linear programs: estimation and policy learning Does AI help humans make better decisions? A statistical evaluation framework for experimental and observational studies

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T01:02:21.153493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:21.153493Z digest=sha256:6becd44ce00acdfd2c2d09abfa85b7d1acb109d468887b38754414f7ed9db98a

Observation 55132055-5d7a-4bd5-afee-558f94e878e1 · inbound

Learning What Evaluators Value: A Reliable Approach to Modeling Evaluator Preferences cites this paper.

Learning What Evaluators Value: A Reliable Approach to Modeling Evaluator Preferences Does AI help humans make better decisions? A statistical evaluation framework for experimental and observational studies

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-20T20:08:58.752811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-20T20:04:53.983505Z digest=sha256:708a742b0b587f8031c926f08dc3b7171491e0b835abb943a60121212b3b2e7d