Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
CosmoFlow: Using Deep Learning to Learn the Universe at Scale
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1808.04728.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T10:47:27.807503Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-06-30T15:14:47.283433Z
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 9b68fffb-7c57-4caf-8e9a-4f04dc7583be · inbound
Cosmological parameter estimation from large-scale structure deep learning cites this paper.
Cosmological parameter estimation from large-scale structure deep learning CosmoFlow: Using Deep Learning to Learn the Universe at Scale
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T10:47:27.807503Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d9f0527-73fc-4a19-9a9a-c88766d20f1b · inbound
Cosmological constraints from neighbor-density-weighted marked correlation functions cites this paper.
Cosmological constraints from neighbor-density-weighted marked correlation functions CosmoFlow: Using Deep Learning to Learn the Universe at Scale
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T03:30:17.320062Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4d301c29-360b-4f99-9e69-abc9c0aefb7c · inbound
Cosmological constraints from neighbor-density-weighted marked correlation functions cites this paper.
Cosmological constraints from neighbor-density-weighted marked correlation functions CosmoFlow: Using Deep Learning to Learn the Universe at Scale
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T15:14:47.284582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.