Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
ERGO-ML I: Inferring the assembly histories of IllustrisTNG galaxies from integral observable properties via invertible neural networks
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2202.06967.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T22:21:35.340587Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-13T04:49:20.506178Z
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 111ddbfa-d3ac-4cd8-90c8-99ad7349fe3c · inbound
Learning from galactic rotation curves: a neural network approach cites this paper.
Learning from galactic rotation curves: a neural network approach ERGO-ML I: Inferring the assembly histories of IllustrisTNG galaxies from integral observable properties via invertible neural networks
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T22:21:35.340587Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84311883-8ab8-47ae-b6aa-6cb387d4ee99 · inbound
Performance of morphological classifiers for galaxy mergers compared to current machine learning methods cites this paper.
Performance of morphological classifiers for galaxy mergers compared to current machine learning methods ERGO-ML I: Inferring the assembly histories of IllustrisTNG galaxies from integral observable properties via invertible neural networks
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-07-13T04:49:20.509849Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.