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Paper Citation Record · LEDGER

Agri-GNN: A Novel Genotypic-Topological Graph Neural Network Framework Built on GraphSAGE for Optimized Yield Prediction

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.13037.

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

pith.paper-citation-record.v1
2310.13037 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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:21:38.683019Z

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

8
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 8063cf50-1d75-40ad-8bd8-758789b54b8b · inbound

Robust soybean seed yield estimation using high-throughput ground robot videos cites this paper.

Robust soybean seed yield estimation using high-throughput ground robot videos Agri-GNN: A Novel Genotypic-Topological Graph Neural Network Framework Built on GraphSAGE for Optimized Yield Prediction

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T23:21:38.683019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:21:38.683019Z digest=sha256:ac1c531522b31da7bc6b63852837ed2302d183ab122ef5d6f645d138b3e71f85

Observation 11420e0f-aab1-4351-ab7e-2df12670f9d8 · inbound

SEAGAN: domain-Specific and Edge-Aware Graph Attention Network for Dynamic Plant Processes cites this paper.

SEAGAN: domain-Specific and Edge-Aware Graph Attention Network for Dynamic Plant Processes Agri-GNN: A Novel Genotypic-Topological Graph Neural Network Framework Built on GraphSAGE for Optimized Yield Prediction

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-06-26T20:49:57.078375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T20:47:53.541906Z digest=sha256:76b8323322f1be7f5baa20781d2d11ee8db5749902a236b167050620c7a99575