Paper Citation Record · LEDGER

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

As of 13 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2411.15263.

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

pith.paper-citation-record.v1
2411.15263 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:52:13.969251Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

verified exact17
verified fuzzy5
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b7c31e65-23c4-4cbc-aa61-601ede278ecd · outbound

This paper cites State of nature 2023,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 State of nature 2023,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:52:14.900147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b4c2bf3d-bd8e-4a02-bc4c-8e2bf43d7855 · outbound

This paper cites Reducing nest predation of ground -nesting birds through conditioned food aversion,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Reducing nest predation of ground -nesting birds through conditioned food aversion,

Reference 2

Resolution: metadata mismatch; raw_fallback, observed 2026-08-12T14:52:14.804752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e1d14ec8-90ec-4bce-bf5d-c4b06268bb3b · outbound

This paper cites Revealing the contributions of reproduction and survival to the Europe-wide decline in meadow birds: Review and meta-analysis,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Revealing the contributions of reproduction and survival to the Europe-wide decline in meadow birds: Review and meta-analysis,

Reference 3

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.273491Z

Source-reported events for the cited work

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Observation a1faf6f2-a540-489a-9e34-08c53ed15ff8 · outbound

This paper cites Revisiting an old question: Which predators eat eggs of ground-nesting birds in farmland landscapes?,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Revisiting an old question: Which predators eat eggs of ground-nesting birds in farmland landscapes?,

Reference 4

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Source-reported events for the cited work

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Observation 8fdd1d9f-d317-44c1-a869-002f7906482f · outbound

This paper cites Ecosystem Services Provided by Birds,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Ecosystem Services Provided by Birds,

Reference 5

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.256064Z

Source-reported events for the cited work

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Observation 9ccc1947-d289-49e4-8134-baf32a6b9941 · outbound

This paper cites Bird - mediated effects of pest control services on crop productivity: a global synthesis,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Bird - mediated effects of pest control services on crop productivity: a global synthesis,

Reference 6

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.236036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation af685093-ccb6-4f96-b8f6-2bb8fa61f3d2 · outbound

This paper cites Home ranges and hatching success of threatened Eurasian curlew in north-eastern Europe relates to habitat type: Natural vs. agricultural landscapes,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Home ranges and hatching success of threatened Eurasian curlew in north-eastern Europe relates to habitat type: Natural vs. agricultural landscapes,

Reference 7

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.219464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e8edac69-d506-4f41-88a0-56d8870ff592 · outbound

This paper cites A synthesis of Eurasian Curlew ( Numenius arquata arquata ) demography and population viability to inform its management,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 A synthesis of Eurasian Curlew ( Numenius arquata arquata ) demography and population viability to inform its management,

Reference 8

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.202612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 890762c5-9789-423a-b9f8-d3895dee4b60 · outbound

This paper cites Nest survival of threatened Eurasian Curlew ( Numenius arquata ) breeding at low densities across a human‐modified landscape,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Nest survival of threatened Eurasian Curlew ( Numenius arquata ) breeding at low densities across a human‐modified landscape,

Reference 9

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.183005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 237de433-b86d-44b7-9d3d-637704bb4d6e · outbound

This paper cites Protecting wild bird nests against predators: A systematic review and meta‐analysis of non‐lethal methods,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Protecting wild bird nests against predators: A systematic review and meta‐analysis of non‐lethal methods,

Reference 10

Resolution: verified exact; raw_fallback, observed 2026-08-12T14:52:14.621425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 09b09a59-ee7a-4bc9-a34a-21745e0244d6 · outbound

This paper cites Camera Traps in Animal Ecology,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Camera Traps in Animal Ecology,

Reference 11

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.164989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 42a7b11d-2657-409c-b825-b15a7ff83e3f · outbound

This paper cites Snap happy: camera traps are an effective sampling tool when compared with alternative methods,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Snap happy: camera traps are an effective sampling tool when compared with alternative methods,

Reference 12

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.145520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a502755e-386a-4b99-82f5-0e0e3611af01 · outbound

This paper cites Software to facilitate and streamline camera trap data management: A review,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Software to facilitate and streamline camera trap data management: A review,

Reference 13

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.126711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e82fbe43-f01a-4798-9225-9932a7ce39fd · outbound

This paper cites Removing Human Bottlenecks in Bird Classification Using Camera Trap Images and Deep Learning,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Removing Human Bottlenecks in Bird Classification Using Camera Trap Images and Deep Learning,

Reference 14

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.106898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7ef36950-b053-40d7-b19e-1b3c9fa8b3da · outbound

This paper cites An evaluation of platforms for processing camera -trap data using artificial intelligence,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 An evaluation of platforms for processing camera -trap data using artificial intelligence,

Reference 15

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Source-reported events for the cited work

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Observation c948760d-2e5f-4789-ad27-48bdc40a1e80 · outbound

This paper cites Automatically identifying, counting, and describing wild animals in camera - trap images with deep learning,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Automatically identifying, counting, and describing wild animals in camera - trap images with deep learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:52:14.883567Z

Source-reported events for the cited work

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Observation 76942cb3-524d-40ab-8c70-9212d223fe00 · outbound

This paper cites Scaling‐up camera traps: monitoring the planet’s biodiversity with networks of remote sensors,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Scaling‐up camera traps: monitoring the planet’s biodiversity with networks of remote sensors,

Reference 17

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Source-reported events for the cited work

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Observation 5eece59b-800f-4b30-861e-e2850bb54305 · outbound

This paper cites Efficient Pipeline for Camera Trap Image Review.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Efficient Pipeline for Camera Trap Image Review

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T14:52:13.902422Z

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Observation 855dcec6-ea1d-4c1c-8f0b-3c1ac13aed40 · outbound

This paper cites Pytorch-Wildlife: A Collaborative Deep Learning Framework for Conservation.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Pytorch-Wildlife: A Collaborative Deep Learning Framework for Conservation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T14:52:13.908217Z

Source-reported events for the cited work

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Observation 313d765a-ffc2-4419-889c-e18722447079 · outbound

This paper cites Wildlife Insights: A Platform to Maximize the Potential of Camera Trap and Other Passive Sensor Wildlife Data for the Planet,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Wildlife Insights: A Platform to Maximize the Potential of Camera Trap and Other Passive Sensor Wildlife Data for the Planet,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T14:52:13.913941Z

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Observation c7f60259-1828-4d09-9b58-7e5ac1c8e0d0 · outbound

This paper cites The inaturalist species classification and detection dataset,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 The inaturalist species classification and detection dataset,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:52:14.864141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7eea8eb4-0a5d-426b-94e2-7b36555a1ac6 · outbound

This paper cites Snapshot Serengeti, high - frequency annotated camera trap images of 40 mammalian species in an African savanna,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Snapshot Serengeti, high - frequency annotated camera trap images of 40 mammalian species in an African savanna,

Reference 22

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.045570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6f6124ad-911c-4d5e-8f6d-35abad87bc16 · outbound

This paper cites Model Generalization in Deep Learning Applications for Land Cover Mapping.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Model Generalization in Deep Learning Applications for Land Cover Mapping

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-12T14:52:14.375337Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 50fed9f2-1691-456f-9fe0-40885b19ee04 · outbound

This paper cites Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-12T14:52:14.348552Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e9c3b9ef-c178-4909-affc-41ea41325048 · outbound

This paper cites Camera trapping —Advancing the technology,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Camera trapping —Advancing the technology,

Reference 25

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.026772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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

This paper cites Harnessing Artificial Intelligence for Wildlife Conservation.

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 2026-08-12T06:34:41.77262+00:00.

Observation 31f028a2-4d9c-4cda-8d23-744c2a2109bd · outbound

This paper cites YOLOv10: Real-Time End-to-End Object Detection.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 YOLOv10: Real-Time End-to-End Object Detection

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T14:52:13.952764Z

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Observation 7ba78a02-d35d-4c66-8900-ba85793154e0 · outbound

This paper cites Large scale fine-grained categorization and domain- specific transfer learning,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Large scale fine-grained categorization and domain- specific transfer learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:52:14.843982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 38afa810-3df5-46d1-b206-a0866c536200 · outbound

This paper cites Targeted transfer learning to improve performance in small medical physics datasets,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Targeted transfer learning to improve performance in small medical physics datasets,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:52:14.822956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8b10378d-a482-4fe5-a7ee-a02fea39ab6c · outbound

This paper cites Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server,.

AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10 Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server,

Reference 30

Resolution: verified exact; doi, observed 2026-08-12T14:52:14.009888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.