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Paper Citation Record · LEDGER

Demystifying Practices, Challenges and Expected Features of Using GitHub Copilot

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2309.05687.

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

pith.paper-citation-record.v1
2309.05687 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:00:22.680773Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T18:29:46.436547Z

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 03b259bc-e970-47a4-ab82-5eb7b3e537b1 · inbound

CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports cites this paper.

CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports Demystifying Practices, Challenges and Expected Features of Using GitHub Copilot

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T06:00:22.680773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:00:22.680773Z digest=sha256:047eb23928c49d72b1d530750c8fbccd16dcccaced73e03ef1323f53d8893357

Observation d7ad9ba8-bf2a-44da-ab64-8c263b7c3ec8 · inbound

The Impact of Generative AI on Code Expertise Models: An Exploratory Study cites this paper.

The Impact of Generative AI on Code Expertise Models: An Exploratory Study Demystifying Practices, Challenges and Expected Features of Using GitHub Copilot

Reference 2023

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T18:29:46.519614Z

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.

source=pdf_text observed=2026-08-06T18:29:46.012683Z digest=sha256:3b23be07d6fc0a75fa2270a4d9c1be0f1b611879e3a2ebb498b4b3351cc3d786