Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Actual Physics behind Mono-X
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1805.11637.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T04:54:12.779002Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T04:54:18.607518Z
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 b72e47fa-991d-4533-8b1a-e75955afbc23 · inbound
Agentic Re-Casting using Agentic Re-Simulations cites this paper.
Agentic Re-Casting using Agentic Re-Simulations Actual Physics behind Mono-X
Reference 209
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T04:29:20.421023Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc771ed3-191d-49a1-91c5-46b610ab65be · inbound
Neural Control Variates at LO and NLO cites this paper.
Neural Control Variates at LO and NLO Actual Physics behind Mono-X
Reference 111
- Resolution
- unresolved
- no resolver link, observed 2026-07-30T18:12:22.076976Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fb508938-ee79-457e-a0de-d529fc9fc29c · inbound
Mono-X Signal Characterization from Two-component Dark Matter Using a Convolutional Neural Network cites this paper.
Mono-X Signal Characterization from Two-component Dark Matter Using a Convolutional Neural Network Actual Physics behind Mono-X
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T04:54:18.610681Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.