Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Case Study of Scalable Content Annotation Using Multi-LLM Consensus and Human Review
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.17620.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:16:14.716525Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T12:52:53.254693Z
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 0d986450-4dfb-430f-a11a-36d2e1872e7b · inbound
Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration cites this paper.
Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration A Case Study of Scalable Content Annotation Using Multi-LLM Consensus and Human Review
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:16:14.716525Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 61d33abe-c9fc-4cee-9467-8f8dec989d71 · inbound
AI-assisted Protocol Information Extraction For Improved Accuracy and Efficiency in Clinical Trial Workflows cites this paper.
AI-assisted Protocol Information Extraction For Improved Accuracy and Efficiency in Clinical Trial Workflows A Case Study of Scalable Content Annotation Using Multi-LLM Consensus and Human Review
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T12:52:53.256673Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.