Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Efficiently analyzing large patient registries with Bayesian joint models for longitudinal and time-to-event data
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2310.03351.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T00:57:13.251056Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-12T06:16:15.957210Z
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 d299739d-47bd-4803-93c9-b1cf9bca4edc · inbound
Debiased Machine Learning for Partially Linear Accelerated Failure Time Models cites this paper.
Debiased Machine Learning for Partially Linear Accelerated Failure Time Models Efficiently analyzing large patient registries with Bayesian joint models for longitudinal and time-to-event data
Reference 117
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-12T00:58:46.155555Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.