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Paper Citation Record · LEDGER

Harnessing Artificial Intelligence for Wildlife Conservation

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.10523.

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

pith.paper-citation-record.v1
2409.10523 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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:29:17.213241Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T14:52:14.309913Z

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 64ea47d9-5541-4844-b689-bd0e8c96486a · inbound

Towards Context-Rich Automated Biodiversity Assessments: Deriving AI-Powered Insights from Camera Trap Data cites this paper.

Towards Context-Rich Automated Biodiversity Assessments: Deriving AI-Powered Insights from Camera Trap Data Harnessing Artificial Intelligence for Wildlife Conservation

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-12T15:29:17.213241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:29:17.213241Z digest=sha256:59427b0b9811a9eab922914b767b48d4ef72d310de8c40787bae8c20305e2548

Observation faa8359d-77b4-4997-9f31-96670a173204 · inbound

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 cites this paper.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Harnessing Artificial Intelligence for Wildlife Conservation

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-08-12T14:52:14.316644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T14:52:13.946396Z digest=sha256:fa6dac93313180adbc16930044ce07ed50b451d234ff09bd8856e1244a24a3a9