Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Predicting COVID-19 pandemic by spatio-temporal graph neural networks: A New Zealand's study
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2305.07731.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:32:50.573472Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T20:32:50.660051Z
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 958e27d0-d768-40de-a098-cd4d8c846e09 · inbound
EpiLLM: Unlocking the Potential of Large Language Models in Epidemic Forecasting cites this paper.
EpiLLM: Unlocking the Potential of Large Language Models in Epidemic Forecasting Predicting COVID-19 pandemic by spatio-temporal graph neural networks: A New Zealand's study
Reference 43
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T20:32:50.665869Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.