Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Machine learning in policy evaluation: new tools for causal inference
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1903.00402.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:39:02.080407Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-04T08:09:41.047956Z
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 34594f0c-5591-45c6-849d-cbde1e5eb895 · inbound
Late Fusion Multi-task Learning for Semiparametric Inference with Nuisance Parameters cites this paper.
Late Fusion Multi-task Learning for Semiparametric Inference with Nuisance Parameters Machine learning in policy evaluation: new tools for causal inference
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:39:02.080407Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5bcfbd2b-0984-436e-94f8-6142bee38e10 · inbound
Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution cites this paper.
Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution Machine learning in policy evaluation: new tools for causal inference
Reference 112
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T05:45:21.245443Z
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.
Observation 58b1940f-601e-4014-acdf-35b381276bc5 · inbound
A Test for Treatment Heterogeneity under a Distributional Difference-in-Difference Framework cites this paper.
A Test for Treatment Heterogeneity under a Distributional Difference-in-Difference Framework Machine learning in policy evaluation: new tools for causal inference
Reference 154
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T08:09:41.049744Z
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.