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Paper Citation Record · LEDGER

GPU-Accelerated DCOPF using Gradient-Based Optimization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.13191.

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

pith.paper-citation-record.v1
2406.13191 v3

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T17:54:24.517112Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 d8774710-71b0-49d4-bcb0-e5fcc4ffd7ac · inbound

Activate the Dual Cones: A Tight Reformulation of Conic ACOPF Constraints cites this paper.

Activate the Dual Cones: A Tight Reformulation of Conic ACOPF Constraints GPU-Accelerated DCOPF using Gradient-Based Optimization

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-02T17:54:24.517112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T17:54:24.517112Z digest=sha256:f39fd647847da795e8a4bd86d4e7d81e550bb82c9e4cbb4f0a80fe0fae1454a2

Observation 90710590-eb1e-49d7-9822-465bb1dba0fe · inbound

Exploring the potential of ChatGPT for feedback and evaluation in experimental physics cites this paper.

Exploring the potential of ChatGPT for feedback and evaluation in experimental physics GPU-Accelerated DCOPF using Gradient-Based Optimization

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-13T21:36:14.566306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T21:36:14.566306Z digest=sha256:06451f1d55fbfb6c50ba43536077b8046e3e93b3e752b2f3b1a9fd2a0e3ce390