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Paper Citation Record · LEDGER

Self-Normalizing Foundation Model for Enhanced Multi-Omics Data Analysis in Oncology

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.08226.

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

pith.paper-citation-record.v1
2405.08226 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 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:54:51.780336Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:06:44.262306Z

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 f801d821-fdd2-4b84-853a-8c4af2ae1905 · inbound

Artificial Intelligence for Central Dogma-Centric Multi-Omics: Challenges and Breakthroughs cites this paper.

Artificial Intelligence for Central Dogma-Centric Multi-Omics: Challenges and Breakthroughs Self-Normalizing Foundation Model for Enhanced Multi-Omics Data Analysis in Oncology

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-11T13:54:51.780336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:54:51.780336Z digest=sha256:5f088de996f9212a2629a707c14774d78ac92e7d16706c2c66ea2b24049469dc

Observation 326931bf-8b63-4410-b99b-514bc3b8ae06 · inbound

RePercENT: Scaling Disentangled Representation Learning Beyond Two Modalities cites this paper.

RePercENT: Scaling Disentangled Representation Learning Beyond Two Modalities Self-Normalizing Foundation Model for Enhanced Multi-Omics Data Analysis in Oncology

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-02T07:06:44.264144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-28T07:10:11.983382Z digest=sha256:a726fdb6738659827bceac7535eaf25e5f30654c685f5112a87884a57b45ecb2