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Paper Citation Record · LEDGER

Advancing Retail Data Science: Comprehensive Evaluation of Synthetic Data

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.13130.

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

pith.paper-citation-record.v1
2406.13130 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:24:07.693168Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T21:10:09.210912Z

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 3e457781-b234-4d24-a197-1814a5f39c9e · inbound

Generating Realistic Multi-Beat ECG Signals cites this paper.

Generating Realistic Multi-Beat ECG Signals Advancing Retail Data Science: Comprehensive Evaluation of Synthetic Data

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T20:24:07.693168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:24:07.693168Z digest=sha256:55a1075b2d454f71f1b22a93d3027e7d9165105fdec413f8e240bff48fd2b8ec

Observation f6b0f0b6-29fd-4918-b284-d06a835e04c0 · inbound

When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification? cites this paper.

When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification? Advancing Retail Data Science: Comprehensive Evaluation of Synthetic Data

Reference 125

Resolution
verified exact
arxiv_id, observed 2026-07-04T21:10:09.212734Z

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.

source=arxiv_source observed=2026-06-25T19:03:59.234023Z digest=sha256:20f7246ccef003250d2f53cef898e96e3fc8c0bc94afcecd0ca647fe7b3fa851