Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T10:29:39.217363Z
Paper Citation Record · LEDGER
Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples
As of 9 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2508.00089.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
7 of 7 outbound references displayed
- verified exact0
- verified fuzzy4
- unresolved3
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation cfb2f225-bca9-44f1-8e97-b2900f006bbe · outbound
This paper cites big data.
Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples big data
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:29:39.307755Z
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.
Observation a7f35427-7d47-4593-8b6f-46bead4b6621 · outbound
This paper cites an unresolved cited work.
Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T10:29:39.296735Z
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.
Observation 70fdee61-3b23-42bc-9fd2-94c51d6bec22 · outbound
This paper cites response variable.
Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples response variable
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:29:39.284838Z
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.
Observation 2467054c-1d49-4488-93fa-b3b4caa1f81e · outbound
This paper cites First, 10 base covariates (𝑉1, ⋯ , 𝑉7) were generated independently following standard normal distributions.
Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples First, 10 base covariates (𝑉1, ⋯ , 𝑉7) were generated independently following standard normal distributions
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:29:39.274458Z
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.
Observation f5fa3d84-a10d-4ccb-9ca1-086bb1fb308d · outbound
This paper cites nonprobability sample.
Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples nonprobability sample
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:29:39.264656Z
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.
Observation f662e37b-df65-47ac-ac8a-f82db2af7cba · outbound
This paper cites an unresolved cited work.
Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T10:29:39.255055Z
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.
Observation ae3f0d36-ed05-41d7-a7f1-a71237f4e5f4 · outbound
This paper cites Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients.
Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients
Reference 1997
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:29:39.217363Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.