Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2202.01723.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:31:41.752267Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T21:45:13.900627Z
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 8468dd60-c24b-4921-9716-4d5757838bb8 · inbound
DeepVIVONet: Using deep neural operators to optimize sensor locations with application to vortex-induced vibrations cites this paper.
DeepVIVONet: Using deep neural operators to optimize sensor locations with application to vortex-induced vibrations Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T21:45:13.908155Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 6ad10d21-1820-4b64-9992-c2fc69be2625 · inbound
Operator Learning for Reconstructing Flow Fields from Sparse Measurements: an Energy Transformer Approach cites this paper.
Operator Learning for Reconstructing Flow Fields from Sparse Measurements: an Energy Transformer Approach Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:31:41.752267Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.