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Paper Citation Record · LEDGER

Multi-component Dark Matter in a Simplified E$_6$SSM Model

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2007.10966.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2007.10966 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:54:27.447768Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T04:54:18.442368Z

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 166e81e5-734e-4f4f-bf21-2c2b71237a6e · inbound

Prospecting bipartite Dark Matter through Gravitational Waves cites this paper.

Prospecting bipartite Dark Matter through Gravitational Waves Multi-component Dark Matter in a Simplified E$_6$SSM Model

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-11T05:54:27.447768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:54:27.447768Z digest=sha256:abe73e34d485c830cd43945b0d1da53d090235a40bd5efd0d973787c2b638acc

Observation ff4ec12d-9bae-43f7-8be6-edae9f05594a · 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 Multi-component Dark Matter in a Simplified E$_6$SSM Model

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-05T04:54:18.445264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T04:54:14.036320Z digest=sha256:c0d2ae3c36e0d28be13572d1cdfedb152b9b570f97a0de25ac58f0e8c8a7bc62