Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.11854.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:32:31.651069Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T03:12:28.770401Z
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 8b5f9c3f-74c8-4e18-9f95-f9fa4d1172ee · inbound
FoNE: Precise Single-Token Number Embeddings via Fourier Features cites this paper.
FoNE: Precise Single-Token Number Embeddings via Fourier Features When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T03:12:28.772920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e1b50853-e204-44b5-864d-d581fed0823b · inbound
LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment cites this paper.
LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:32:31.651069Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.