Paper Citation Record · LEDGER

Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2310.18729.

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

pith.paper-citation-record.v1
2310.18729 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:25:23.009408Z

measured 1 of 1 external citation measurements

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

5
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 399c5f93-4e48-43dc-a5d6-2dcef2fecda7 · inbound

Analyzing Images of Legal Documents: Toward Multi-Modal LLMs for Access to Justice cites this paper.

Analyzing Images of Legal Documents: Toward Multi-Modal LLMs for Access to Justice Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T14:34:14.278911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3653d85-1b27-477d-ad12-584145edf4fc · inbound

From Assistance to Autonomy -- A Researcher Study on the Potential of AI Support for Qualitative Data Analysis cites this paper.

From Assistance to Autonomy -- A Researcher Study on the Potential of AI Support for Qualitative Data Analysis Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T20:46:45.972819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c47c8d1-97ae-4553-901f-ade8071f296a · inbound

LLM-TA: An LLM-Enhanced Thematic Analysis Pipeline for Transcripts from Parents of Children with Congenital Heart Disease cites this paper.

LLM-TA: An LLM-Enhanced Thematic Analysis Pipeline for Transcripts from Parents of Children with Congenital Heart Disease Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T14:51:57.430825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ae71448-ba3c-484a-b8d9-305c61527e23 · inbound

Occ-LLM: Enhancing Autonomous Driving with Occupancy-Based Large Language Models cites this paper.

Occ-LLM: Enhancing Autonomous Driving with Occupancy-Based Large Language Models Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T15:33:48.321545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b579006c-2634-46b4-9540-34f61fa9a464 · inbound

VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents cites this paper.

VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:37:13.903092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1b2856d7-4c4e-40cf-82d5-ab379934c91d · inbound

Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study cites this paper.

Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-16T04:25:23.009408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.