Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Fully Automated Pipeline for Conversational Discourse Annotation: Tree Scheme Generation and Labeling with Large Language Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2504.08961.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:16:53.710371Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T05:33:28.947521Z
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 dc7f618f-cfde-40e4-9b06-6e25b459551b · inbound
Analyzing Biases in Political Dialogue: Tagging U.S. Presidential Debates with an Extended DAMSL Framework cites this paper.
Analyzing Biases in Political Dialogue: Tagging U.S. Presidential Debates with an Extended DAMSL Framework A Fully Automated Pipeline for Conversational Discourse Annotation: Tree Scheme Generation and Labeling with Large Language Models
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:16:53.710371Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9df11ec7-bed3-4f62-a38e-7bda1dec6d9f · inbound
Intent Matters: Enhancing AI Tutoring with Fine-Grained Pedagogical Intent Annotation cites this paper.
Intent Matters: Enhancing AI Tutoring with Fine-Grained Pedagogical Intent Annotation A Fully Automated Pipeline for Conversational Discourse Annotation: Tree Scheme Generation and Labeling with Large Language Models
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T05:33:29.040064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.