Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Rediscovering orbital mechanics with machine learning
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2202.02306.
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, observed 2026-08-06T19:26:34.825210Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T08:54:15.936031Z
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 25adec6b-2785-4703-8295-d44ebc86464e · inbound
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems cites this paper.
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems Rediscovering orbital mechanics with machine learning
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T08:54:15.938900Z
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 17092829-eae4-4fb7-a923-b76c4980d42a · inbound
On the definition and importance of interpretability in scientific machine learning cites this paper.
On the definition and importance of interpretability in scientific machine learning Rediscovering orbital mechanics with machine learning
Reference 39
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-22T14:11:38.671325Z
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 b1e89266-5b10-4472-8d54-68025b3e7272 · inbound
$\mathcal{CP}$-Analyses with Symbolic Regression cites this paper.
$\mathcal{CP}$-Analyses with Symbolic Regression Rediscovering orbital mechanics with machine learning
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:26:34.825210Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3b0c4bb-71a2-4fb0-88e1-3acd62b157b2 · inbound
Predicting intermediate-mass black hole formation in star clusters with machine learning cites this paper.
Predicting intermediate-mass black hole formation in star clusters with machine learning Rediscovering orbital mechanics with machine learning
Reference 91
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-22T09:21:21.152886Z
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.