Pith. sign in

Paper Citation Record · LEDGER

Policy Learning for Optimal Dynamic Treatment Regimes with Observational Data

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.00221.

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

pith.paper-citation-record.v1
2404.00221 v7

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:08:49.978135Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:45:20.082288Z

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 20ec11a7-47df-472e-a543-a2edb97804b4 · inbound

Evaluating Program Sequences with Double Machine Learning: An Application to Labor Market Policies cites this paper.

Evaluating Program Sequences with Double Machine Learning: An Application to Labor Market Policies Policy Learning for Optimal Dynamic Treatment Regimes with Observational Data

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T01:08:49.978135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:08:49.978135Z digest=sha256:0a41c910e48760bc686dca31ae5e2e318bde1a141387bd3556fd4e79e3ede2a0

Observation 031a9b9b-bf16-43b7-830f-22e5cc4d3a5e · inbound

Minimax and Bayes Optimal Best-Arm Identification cites this paper.

Minimax and Bayes Optimal Best-Arm Identification Policy Learning for Optimal Dynamic Treatment Regimes with Observational Data

Reference 71

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:45:20.182220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T21:45:18.606913Z digest=sha256:7f91995256582dad2cbfc50a8fe605e45ed275dca0a45db4fd8d26485e0fc4bb