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Paper Citation Record · LEDGER

A decorrelation method for general regression adjustment in randomized experiments

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.10076.

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

pith.paper-citation-record.v1
2311.10076 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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:07:15.321164Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T21:26:14.249501Z

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 8b40b379-9911-4a4b-a9f4-5f04b62798be · inbound

Design-based edge-level causal inference with machine learning assisted covariate adjustment cites this paper.

Design-based edge-level causal inference with machine learning assisted covariate adjustment A decorrelation method for general regression adjustment in randomized experiments

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:26:14.250847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T17:04:43.856708Z digest=sha256:8f597e421825aedbc1cae1e455b38fc915780cc22729021dccebc55ab4d506ad

Observation 25ab0ab6-7127-4f23-9280-fc817756977b · inbound

A Design-Based Minimax Theory for Network Experiments cites this paper.

A Design-Based Minimax Theory for Network Experiments A decorrelation method for general regression adjustment in randomized experiments

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-06T14:07:15.321164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:07:15.321164Z digest=sha256:a36d770d9f717b118c7801741396b040e2ad13f2a5a55f9c3cc3065fab85a9d9