Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecasting
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2010.00399.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:34:19.402826Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T07:32:31.332529Z
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 94d40aaf-134b-49fa-91c1-61063e0c2397 · inbound
Deep Koopman operator framework for causal discovery in nonlinear dynamical systems cites this paper.
Deep Koopman operator framework for causal discovery in nonlinear dynamical systems Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecasting
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:34:19.402826Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 421cd855-6498-4e5b-872a-d8bef7c12550 · inbound
Reduced-Order Surrogates for Forced Flexible Mesh Coastal-Ocean Models cites this paper.
Reduced-Order Surrogates for Forced Flexible Mesh Coastal-Ocean Models Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecasting
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T07:32:31.335020Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 2d408b2e-1c74-4740-93b3-6567af19b4b4 · inbound
Non-intrusive Learning of Physics-Informed Spatio-temporal Surrogate for Accelerating Design cites this paper.
Non-intrusive Learning of Physics-Informed Spatio-temporal Surrogate for Accelerating Design Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecasting
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T13:20:26.718753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.