Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
An LLM-based Knowledge Synthesis and Scientific Reasoning Framework for Biomedical Discovery
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.18626.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T23:45:43.699598Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 25b0c4db-17b5-4689-a26d-b608c460816e · inbound
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models cites this paper.
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models An LLM-based Knowledge Synthesis and Scientific Reasoning Framework for Biomedical Discovery
Reference 164
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T21:20:59.363990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 5b5ec3b5-a176-4340-970f-e533016d0923 · inbound
Scientific Hypothesis Generation and Validation: Methods, Datasets, and Future Directions cites this paper.
Scientific Hypothesis Generation and Validation: Methods, Datasets, and Future Directions An LLM-based Knowledge Synthesis and Scientific Reasoning Framework for Biomedical Discovery
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T23:45:43.699598Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 96269c70-d540-4899-8c1c-913d704751fd · inbound
From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines cites this paper.
From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines An LLM-based Knowledge Synthesis and Scientific Reasoning Framework for Biomedical Discovery
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-06-27T17:31:07.552319Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation bd4ed790-cee2-4b28-b77f-37241f87ed7e · inbound
From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines cites this paper.
From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines An LLM-based Knowledge Synthesis and Scientific Reasoning Framework for Biomedical Discovery
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:03:29.646127Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.