Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Physics-Informed Gaussian Process Regression for Probabilistic States Estimation and Forecasting in Power Grids
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2010.04591.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T21:08:21.039244Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T09:49:44.672684Z
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 f3f4d56e-780a-426a-88ad-7a4390483a10 · inbound
Quantum multi-output Gaussian Processes based Machine Learning for Line Parameter Estimation in Electrical Grids cites this paper.
Quantum multi-output Gaussian Processes based Machine Learning for Line Parameter Estimation in Electrical Grids Physics-Informed Gaussian Process Regression for Probabilistic States Estimation and Forecasting in Power Grids
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T21:08:21.039244Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 17c26206-8d47-419a-8581-7e8a030fcfb1 · inbound
Synergizing Physically Constrained MCMC and Chemical-Informed Gaussian Processes for Reaction Network Discovery cites this paper.
Synergizing Physically Constrained MCMC and Chemical-Informed Gaussian Processes for Reaction Network Discovery Physics-Informed Gaussian Process Regression for Probabilistic States Estimation and Forecasting in Power Grids
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T09:49:44.673911Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.