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Paper Citation Record · LEDGER

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning

As of 18 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2506.01073.

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

pith.paper-citation-record.v1
2506.01073 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:55:58.278105Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

27 of 27 outbound references displayed

  • verified exact0
  • verified fuzzy22
  • unresolved4
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 248b07e9-f57f-49a4-bb2b-ad21187aca5d · outbound

This paper cites Cancer/Radiotherapie, 2024.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Cancer/Radiotherapie, 2024

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:01.415678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7cfea701-7f0d-4374-8c1e-ab8940547218 · outbound

This paper cites Journal of Applied Clinical Medical Physics, 2020.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Journal of Applied Clinical Medical Physics, 2020

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:01.350595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8506493c-4e97-4e84-9d93-7750c673f14d · outbound

This paper cites Radiation Oncology, 2022.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Radiation Oncology, 2022

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:01.236316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a58eb2cd-dcee-4374-aade-44af3a902672 · outbound

This paper cites Journal of Applied Clinical Medical Physics, 2023.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Journal of Applied Clinical Medical Physics, 2023

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:01.089961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.374963Z digest=sha256:c0c83c2e40bf46364aefbc2d94b862f05a5a6e43a50488bf9e2c520ee6bb68c1

Observation 530c2d51-80fb-480c-9002-1167a8cb96b3 · outbound

This paper cites Medical physics, 2022.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Medical physics, 2022

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:00.982999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.414925Z digest=sha256:bcc6e87e12abc496af675b6d088e99a4ec147880089573e8ba9071434e13b501

Observation de5d65a0-8a49-4ab6-bbc6-f0dde1e8bf2d · outbound

This paper cites Nature Communications, 2024.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Nature Communications, 2024

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:00.918990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.445297Z digest=sha256:dd7ea69aabebf50df47692b2e11a1d57308dceeb21158a1f31dc28992c6b159b

Observation 75010fb0-1412-403b-b366-e2e371e3647a · outbound

This paper cites Medclip: Contrastive learning from unpaired medical images and text.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Medclip: Contrastive learning from unpaired medical images and text

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:00.849008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.550206Z digest=sha256:7834fe46b4039990289665f0a7dd8825e4b6deb95d561385458b9a3efa8e8d0e

Observation 9cb9bbfa-4601-4d93-b511-dbcd33aa1706 · outbound

This paper cites an unresolved cited work.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:56:00.786045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.609973Z digest=sha256:38b0045041b96076a5884d335576f0b864da561bc1eda1a34450716af8335e32

Observation 3269e957-1624-4221-950b-22cc3f2e7db2 · outbound

This paper cites Medical Image Analysis, 2022.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Medical Image Analysis, 2022

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:00.721748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.635913Z digest=sha256:ac48d52f73204b4928a140a17cd4072f63c3c63d1be3916d086e0c5534dedbcc

Observation 6766ee7c-55ae-4e72-a091-7c50a4016e7d · outbound

This paper cites The Cancer Imaging Archive, 2017.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning The Cancer Imaging Archive, 2017

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:00.625907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.694829Z digest=sha256:1aa2d79b88617a8bf1317522a361b0e8ac59e7c4c3237d57f8c5559bb843d353

Observation 587d9957-f30b-4527-81df-139e490fd162 · outbound

This paper cites EBioMedicine, 2020.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning EBioMedicine, 2020

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:00.465559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.760528Z digest=sha256:0bdb82fde21c0b887fb4fd03254aff6f1f06bba446f9898442bb0d4d6df2a927

Observation b91fdf75-ee05-4933-ab5d-e7bc772162ef · outbound

This paper cites Cancer Imaging Arch, 2015.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Cancer Imaging Arch, 2015

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:00.260430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.798189Z digest=sha256:d3b75c5aee26d537e6302da6a92298b3e1eaaf5e9536a96976d650c103f5d503

Observation b619a7b0-d0c6-4cdd-a55f-d70d9616fe5a · outbound

This paper cites The Cancer Imaging Archive, 2020.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning The Cancer Imaging Archive, 2020

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:00.084487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.825747Z digest=sha256:0835c1044a983e618a3db440b424a7e71f322ba3def1e5ae9e453020045c59d3

Observation 569845c0-9b70-4fcc-9bf5-d9ac54a9a721 · outbound

This paper cites Radiotherapy and Oncology, 2025.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Radiotherapy and Oncology, 2025

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:55:59.902438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.855947Z digest=sha256:a84f0a8616300b4985d21521108ff540cdc4971e392955fe16dd2443c07c8daf

Observation 751059d8-1350-4674-b1f9-d5f1470fd497 · outbound

This paper cites Radiology: Artificial Intelligence, 2023.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Radiology: Artificial Intelligence, 2023

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:55:59.751161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:57.891483Z digest=sha256:3341fa4484553dd0442796f6a3b1023eef2ed6e390fa7c5d3ad5c45202164206

Observation b7b1adcd-75a8-491b-a29d-7f0f74e6dc87 · outbound

This paper cites nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T11:55:57.953057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:57.953057Z digest=sha256:c215c5bfd4bf64b7992fab71cdc0f126881ec47b61c4f52b79877f853e90c986

Observation b80166ba-42b2-4e6e-8356-15ca82e21fc2 · outbound

This paper cites STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T11:55:57.994806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:57.994806Z digest=sha256:02f4934c6aef03a3b0962ccd9705778cf92d4b836f299d96279fea4f1bff1b19

Observation 3c2973f5-988c-42ce-88a7-c1e57af0b4f7 · outbound

This paper cites an unresolved cited work.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:55:59.596933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:58.022908Z digest=sha256:ded5dd3090d8f7b9c06518522af7cd677d5d27d237a9295cec2122753c23d590

Observation 1f6c6c9c-4fe1-4d4a-bfc8-ce063c905169 · outbound

This paper cites Segreg: Segmenting oars by registering mr images and ct annotations.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Segreg: Segmenting oars by registering mr images and ct annotations

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:55:59.402568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:58.053596Z digest=sha256:f5e371f180d7ab0fbeda6604d460abcc08e98993aedf277c49fc8d9e27b52c97

Observation a077af51-c97d-45b6-9909-94c8ec036058 · outbound

This paper cites Medical Physics, 2021.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Medical Physics, 2021

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:55:59.193115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4002ab39-7c49-4bba-ba84-8df2cf3d0926 · outbound

This paper cites Journal of applied clinical medical physics, 2022.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Journal of applied clinical medical physics, 2022

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:55:58.969841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:58.118536Z digest=sha256:0bfeac8412285650f7d229f0e3c64210f7c4e25c3eca59d93e89c78c28b33a68

Observation 3d10af85-c219-4087-a955-c78c90759353 · outbound

This paper cites Medical physics,.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Medical physics,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:55:58.822525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:58.149322Z digest=sha256:4dbfa33b39c4f6ab0036b4bed5093663c20b151e108ac1214a55e938f2393cd4

Observation 5f6fd1c9-da8e-4ac9-af31-39c5ea334be4 · outbound

This paper cites Physics in Medicine & Biology, 2024.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Physics in Medicine & Biology, 2024

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:55:58.590047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:58.215610Z digest=sha256:c1c7eef1c8d7ed91ac5e4871a093a76a5e5d94559c385a8af684ff62597dd973

Observation 06a3838d-a591-45f5-ac6c-1dcf8379c92f · outbound

This paper cites International Journal of Imaging Systems and Technology, 2022.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning International Journal of Imaging Systems and Technology, 2022

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:55:58.532066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:58.241322Z digest=sha256:a718dc505b347054b5a1acafe3b80486e1fb0950bd039400c2766836390acebb

Observation 9b8b518b-aa55-48f4-8e92-4e56d1d246bf · outbound

This paper cites Medical physics, 2020.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Medical physics, 2020

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:55:58.464331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:58.262935Z digest=sha256:cbeb82353c020e685878b6cb01138d94751c57198096fc9db84078cb5ae2fa10

Observation f412cbdb-df7f-4a0d-8427-0671a723f047 · outbound

This paper cites Journal of Medical Imaging, 2024.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Journal of Medical Imaging, 2024

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:55:58.426331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:58.278105Z digest=sha256:16120553a5124a7325b648a64f236eed98895207f4775c0dd704b29e54d9f294

Observation 832bcbe5-700b-481c-90d5-a68a885ed781 · outbound

This paper cites 7028-7042.

A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning 7028-7042

Reference 2021

Resolution
parse uncertain
raw_fallback, observed 2026-08-07T11:55:58.752433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:55:58.179843Z digest=sha256:f820a333af384d36d686cb856223b4c619143b884b0ef4445f35634e0a47d8f5

Pith citing papers

No inbound Pith citation observations are available.