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Paper Citation Record · LEDGER

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios

As of 15 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2412.05871.

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

pith.paper-citation-record.v1
2412.05871 v3

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:19:09.590984Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3b70a76f-5115-417a-953d-52ed31c9b9bc · outbound

This paper cites An outlook on the future marine traffic management system for autonomous ships,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios An outlook on the future marine traffic management system for autonomous ships,

Reference 1

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Observation a7e57845-60f5-43e6-a881-5f5e2cdf7ce5 · outbound

This paper cites Developments in global seatrade and container shipping markets: their effects on the port industry and private sector involve- ment,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Developments in global seatrade and container shipping markets: their effects on the port industry and private sector involve- ment,

Reference 2

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Source-reported events for the cited work

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Observation af19c7d0-fe8c-4308-8633-f234dad6dd57 · outbound

This paper cites Internet of things for smart ports: Technologies and challenges,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Internet of things for smart ports: Technologies and challenges,

Reference 3

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Source-reported events for the cited work

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Observation 5463e840-daea-4330-af26-f690873356d9 · outbound

This paper cites Multi-stage and multi- topology analysis of ship traffic complexity for probabilistic collision detection,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Multi-stage and multi- topology analysis of ship traffic complexity for probabilistic collision detection,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation a33fa594-3f44-4941-87cd-08890609d98e · outbound

This paper cites A sidelobe-aware small ship detection network for synthetic aperture radar imagery,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios A sidelobe-aware small ship detection network for synthetic aperture radar imagery,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 79cab9df-a437-4dcb-890f-0495d951de34 · outbound

This paper cites Sensors and ai techniques for situational awareness in au- tonomous ships: A review,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Sensors and ai techniques for situational awareness in au- tonomous ships: A review,

Reference 6

Resolution
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Source-reported events for the cited work

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Observation 56902d68-e440-47cb-800a-527998f0c168 · outbound

This paper cites The ocean-going autonomous ship—challenges and threats,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios The ocean-going autonomous ship—challenges and threats,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation a874b93d-f68f-4516-a5e2-26237b0ac898 · outbound

This paper cites Weather-aware object detection method for maritime surveillance systems,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Weather-aware object detection method for maritime surveillance systems,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 0e670e2c-843f-42c9-9caf-efad960c8abd · outbound

This paper cites Object detection in a maritime environment: Performance evaluation of background subtraction methods,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Object detection in a maritime environment: Performance evaluation of background subtraction methods,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b2e7979d-86b0-4551-ae14-86b4aa510f98 · outbound

This paper cites Ship detection in high-resolution optical imagery based on anomaly detector and local shape feature,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Ship detection in high-resolution optical imagery based on anomaly detector and local shape feature,

Reference 10

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Source-reported events for the cited work

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Observation 5f6135f4-bcf3-43d0-b61e-61a5880244f8 · outbound

This paper cites How big data enriches maritime research–a critical review of automatic identification system (ais) data applications,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios How big data enriches maritime research–a critical review of automatic identification system (ais) data applications,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 90806b77-9ef1-46f0-89d2-3e9069d0f7d2 · outbound

This paper cites Ship detection with high-resolution hf skywave radar,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Ship detection with high-resolution hf skywave radar,

Reference 12

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Source-reported events for the cited work

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Observation 8e5fe798-2b95-4523-bacc-d14bcacacb28 · outbound

This paper cites Conservation science and policy applications of the marine vessel automatic identification system (ais)—a review,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Conservation science and policy applications of the marine vessel automatic identification system (ais)—a review,

Reference 13

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f89f476b-1006-4c72-8e67-7a3367134c17 · outbound

This paper cites Ship de- tection with spectral analysis of synthetic aperture radar: A comparison of new and well-known algorithms,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Ship de- tection with spectral analysis of synthetic aperture radar: A comparison of new and well-known algorithms,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 53e8fc17-b7d8-40d9-b00a-3bfa82c6b0c2 · outbound

This paper cites Ship detection for visual maritime surveillance from non-stationary platforms,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Ship detection for visual maritime surveillance from non-stationary platforms,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 0f0464a7-50fa-4f9e-9158-09948c450780 · outbound

This paper cites Research of target detection and classification techniques using millimeter-wave radar and vision sensors,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Research of target detection and classification techniques using millimeter-wave radar and vision sensors,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation cf31c9e7-6be5-47b9-bec8-9251a855e8c4 · outbound

This paper cites Dataset and benchmark for ship detection in complex optical remote sensing image,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Dataset and benchmark for ship detection in complex optical remote sensing image,

Reference 17

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Source-reported events for the cited work

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Observation 3b04ebed-471c-4ab4-9890-f0633a10766c · outbound

This paper cites Hrsid: A high-resolution sar images dataset for ship detection and instance segmentation,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Hrsid: A high-resolution sar images dataset for ship detection and instance segmentation,

Reference 18

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Source-reported events for the cited work

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Observation ad99b83e-0d1b-4024-838d-5c725dd3a901 · outbound

This paper cites Sar ship detection dataset (ssdd): Official release and comprehensive data analysis,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Sar ship detection dataset (ssdd): Official release and comprehensive data analysis,

Reference 19

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Source-reported events for the cited work

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Observation 3c2a187e-d8c7-4b37-bd75-862da8df5895 · outbound

This paper cites Object detection and instance segmentation in remote sensing imagery based on precise mask r-cnn,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Object detection and instance segmentation in remote sensing imagery based on precise mask r-cnn,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6fb616e1-2f3e-46ef-a52a-bc050b7acc19 · outbound

This paper cites Hq- isnet: High-quality instance segmentation for remote sensing imagery,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Hq- isnet: High-quality instance segmentation for remote sensing imagery,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 26dbc879-a150-4ca6-ad0b-9911dd9ae7d5 · outbound

This paper cites A high resolution optical satellite image dataset for ship recognition and some new baselines,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios A high resolution optical satellite image dataset for ship recognition and some new baselines,

Reference 22

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Source-reported events for the cited work

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Observation f0f18645-e242-4e0e-967f-82f26f28a351 · outbound

This paper cites Shiprsimagenet: A large-scale fine-grained dataset for ship detection in high-resolution optical remote sensing images,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Shiprsimagenet: A large-scale fine-grained dataset for ship detection in high-resolution optical remote sensing images,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e9b007e5-1fc2-4bdf-89a5-14a79da1935c · outbound

This paper cites Fine-grained recognition for oriented ship against complex scenes in optical remote sensing images,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Fine-grained recognition for oriented ship against complex scenes in optical remote sensing images,

Reference 24

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Source-reported events for the cited work

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Observation 7f29ec59-68c1-4fbc-819c-a45aebc90223 · outbound

This paper cites Seaships: A large-scale precisely annotated dataset for ship detection,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Seaships: A large-scale precisely annotated dataset for ship detection,

Reference 25

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Source-reported events for the cited work

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Observation 670cffe9-de60-467e-bb0d-2fc032fac338 · outbound

This paper cites A discriminatively trained, multiscale, deformable part model,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios A discriminatively trained, multiscale, deformable part model,

Reference 26

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Source-reported events for the cited work

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Observation a16426cc-fd77-48c3-a6c6-45af24f81b57 · outbound

This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Rich feature hierarchies for accurate object detection and semantic segmentation,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation abd7ef27-05f4-4e35-b7b0-67a6d1713f84 · outbound

This paper cites Fast R-CNN.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Fast R-CNN

Reference 28

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Source-reported events for the cited work

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Observation bfd875dc-1f14-4818-8c2f-55a68178faf8 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 22cd9741-6c2b-47a5-94fb-de3e65ea6ad9 · outbound

This paper cites You only look once: Unified, real-time object detection,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios You only look once: Unified, real-time object detection,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c3dbae44-4d2d-472b-b259-da12ad32d403 · outbound

This paper cites Ssd: Single shot multibox detector,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Ssd: Single shot multibox detector,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ad425f73-7c26-4973-9546-b03cfa3775b6 · outbound

This paper cites Focal loss for dense object detection,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Focal loss for dense object detection,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 925be854-35ab-445e-802a-ad368c6406b4 · outbound

This paper cites End-to-end object detection with transformers,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios End-to-end object detection with transformers,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:19:09.700455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T20:19:09.572244Z digest=sha256:6e6261641cc85db619150bdc16b6c59f5e818003a5f9807062f8b1f69c7b59c1

Observation b8e88904-c17e-4533-822c-acc191f5cd59 · outbound

This paper cites Efficientdet: Scalable and efficient object detection,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Efficientdet: Scalable and efficient object detection,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:19:09.685984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T20:19:09.577351Z digest=sha256:461b480809363efa641e26b19dd2124042709e7a8ee752c89786b3e5d2b1b2ca

Observation c7ffa619-04f8-46ea-a941-51763f3d7b09 · outbound

This paper cites YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T20:19:09.581723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:19:09.581723Z digest=sha256:725160403f79dbd66c4442a16fb0200a88b5b7dcc8e06415245b4838e22ac77f

Observation f06f5808-fe63-46ff-ac27-51d3c4ce891d · outbound

This paper cites Yolov9: Learning what you want to learn using programmable gradient information,.

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios Yolov9: Learning what you want to learn using programmable gradient information,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T20:19:09.670594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T20:19:09.586403Z digest=sha256:86a84ec5d6e8651e223e8f15913475446db7664fe6ef2762443ab80139457bf3

Observation e3e93c46-e648-4c45-8d1b-28234285cb2a · outbound

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

MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios YOLOv10: Real-Time End-to-End Object Detection

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T20:19:09.590984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:19:09.590984Z digest=sha256:8c1af294743e71003a31e61a8d04d35717d50fb2c7e4dacb20f24ac0a4e6daa7

Pith citing papers

No inbound Pith citation observations are available.