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Paper Citation Record · LEDGER

PepGB: Facilitating peptide drug discovery via graph neural networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.14665.

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

pith.paper-citation-record.v1
2401.14665 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 2026-08-06T23:48:25.794753Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:48:35.297838Z

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 ca58eb51-6fd4-4a53-b15b-4c3677ccaa9f · inbound

Geometric deep learning assists protein engineering. Opportunities and Challenges cites this paper.

Geometric deep learning assists protein engineering. Opportunities and Challenges PepGB: Facilitating peptide drug discovery via graph neural networks

Reference 77

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:48:35.458885Z

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=arxiv_source observed=2026-08-06T23:48:25.794753Z digest=sha256:33bdfd01d9e86c24f4c24e9243e461b916db6e88b786d2db087c94e9c5eb463b

Observation d16710e4-a410-4f70-9c34-94e2cde18f1f · inbound

AMPBench-MT: A Homology-Controlled Benchmark for Antimicrobial Peptide Potency, Spectrum, and Safety Prediction cites this paper.

AMPBench-MT: A Homology-Controlled Benchmark for Antimicrobial Peptide Potency, Spectrum, and Safety Prediction PepGB: Facilitating peptide drug discovery via graph neural networks

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-01T02:14:44.477738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T02:14:44.477738Z digest=sha256:b669fa164f229c602455f01eb331508a7453fe7efff17c3a9c311305c330d74d