Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Deep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identification
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1812.09444.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T13:09:17.962749Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-14T13:09:18.478782Z
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 820be45f-ae12-422e-9c8a-5b2d25559f18 · inbound
A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems cites this paper.
A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems Deep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identification
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-08-14T13:09:18.485888Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.