Paper Citation Record · LEDGER

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound

As of 18 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 1 inbound Pith citation observation for arXiv:2507.18082.

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

pith.paper-citation-record.v1
2507.18082 v3

Coverage vector

measured 45 of 45 reference resolution

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measured 46 of 46 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T18:55:31.923309Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T18:56:45.973121Z

Reference resolution

45 of 45 outbound references displayed

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External citation measurements

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Outbound references

Observation fccf660d-80bd-4837-a866-a882e46d149f · outbound

This paper cites Making the most of text semantics to improve biomedical vision–language processing.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Making the most of text semantics to improve biomedical vision–language processing

Reference 1

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Observation 662271f1-dc2d-4a40-9a07-255d6f5c0f29 · outbound

This paper cites Global cancer statistics 2022: Globocan estimates of incidence and mortality worldwide for 36 can- cers in 185 countries.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Global cancer statistics 2022: Globocan estimates of incidence and mortality worldwide for 36 can- cers in 185 countries

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.734699Z

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Observation 488e246b-71a7-43c3-8835-1b21f355d20d · outbound

This paper cites Sabuncu, John Guttag, and Adrian V.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Sabuncu, John Guttag, and Adrian V

Reference 3

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Observation d1430622-3caf-45d0-9860-a5fe80483266 · outbound

This paper cites Swin-unet: Unet-like pure transformer for medical image segmentation.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Swin-unet: Unet-like pure transformer for medical image segmentation

Reference 4

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Observation 217f0e0c-d135-430b-b4b4-057d5f12cbae · outbound

This paper cites Domain-controlled prompt learning.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Domain-controlled prompt learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.702621Z

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Observation cfa8c2be-1709-42ab-998a-cbdfefb452ad · outbound

This paper cites SAM on Medical Images: A Comprehensive Study on Three Prompt Modes.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

Reference 6

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Observation c70c769d-3061-44b5-91cc-6f1119b6952b · outbound

This paper cites Does clip benefit visual question answering in the medical domain as much as it does in the general domain?, 2021.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Does clip benefit visual question answering in the medical domain as much as it does in the general domain?, 2021

Reference 7

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Observation 2ec7e583-95b5-488f-a2ba-ae907d07c637 · outbound

This paper cites Clip-adapter: Better vision-language models with feature adapters.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Clip-adapter: Better vision-language models with feature adapters

Reference 8

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Observation a34e7efc-c844-4559-ae89-07ddcd15d286 · outbound

This paper cites 3dsam-adapter: Holistic adaptation of sam from 2d to 3d for promptable medical image segmentation, 2023.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound 3dsam-adapter: Holistic adaptation of sam from 2d to 3d for promptable medical image segmentation, 2023

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.679433Z

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Observation 58647c90-8429-425d-8993-1e7fc455e478 · outbound

This paper cites Cc-sam: Sam with cross-feature attention and context for ultrasound image seg- mentation.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Cc-sam: Sam with cross-feature attention and context for ultrasound image seg- mentation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.669632Z

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Observation ce47e389-03b8-4283-81c4-b4fe216dfef6 · outbound

This paper cites Domain-specific language model pre- training for biomedical natural language processing.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Domain-specific language model pre- training for biomedical natural language processing

Reference 11

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Observation ac5b685c-4584-489b-8dcb-13573ab6079d · outbound

This paper cites Lora: Low- rank adaptation of large language models.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Lora: Low- rank adaptation of large language models

Reference 12

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Observation a2546755-be00-4747-bae1-d07ad559341c · outbound

This paper cites Cascade segmentation framework for pancreatic tumor in ultrasound images.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Cascade segmentation framework for pancreatic tumor in ultrasound images

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.638979Z

Source-reported events for the cited work

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Observation c78b52b3-d4c7-4f97-ad59-ac4edafc875f · outbound

This paper cites Push the boundary of sam: A pseudo-label correction framework for medical segmenta- tion, 2023.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Push the boundary of sam: A pseudo-label correction framework for medical segmenta- tion, 2023

Reference 14

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Observation d0d2106e-b649-418d-830c-2e1d9dd19e09 · outbound

This paper cites nnu-net: a self-configuring method for deep learning-based biomedical image segmen- tation.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound nnu-net: a self-configuring method for deep learning-based biomedical image segmen- tation

Reference 15

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Source-reported events for the cited work

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Observation af097816-3b1b-4273-b2ad-03ebf93fb952 · outbound

This paper cites Endoscopic ultrasound database of the pancreas.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Endoscopic ultrasound database of the pancreas

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.607152Z

Source-reported events for the cited work

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Observation 79898284-c8dc-43ef-a27b-82c77da66385 · outbound

This paper cites Scaling up visual and vision-language representa- tion learning with noisy text supervision.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Scaling up visual and vision-language representa- tion learning with noisy text supervision

Reference 17

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Observation 0bf2d1a2-7f6a-40ab-80fb-eeda21294349 · outbound

This paper cites Maple: Multi-modal prompt learning.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Maple: Multi-modal prompt learning

Reference 18

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Observation bb0c30f0-7a27-46d8-800d-1ed828d1274b · outbound

This paper cites Self-regulating prompts: Foundational model adaptation without forgetting.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Self-regulating prompts: Foundational model adaptation without forgetting

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.578540Z

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Observation 51065ff2-c03d-434e-a71f-bd37dd7a3272 · outbound

This paper cites Learning to Prompt with Text Only Supervision for Vision-Language Models.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Learning to Prompt with Text Only Supervision for Vision-Language Models

Reference 20

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Observation f49b4f46-87e7-479e-bd11-140f8f38ab58 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Doll ´ar, and Ross Girshick.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Berg, Wan-Yen Lo, Piotr Doll ´ar, and Ross Girshick

Reference 21

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Observation 50918e93-f8d5-4b31-9703-97e446eab859 · outbound

This paper cites Transformer les soins de sant ´e gr ˆace `a des mod`eles de langage multimodaux universels, efficaces et ´evolutifs pour l’analyse biom ´edicale.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Transformer les soins de sant ´e gr ˆace `a des mod`eles de langage multimodaux universels, efficaces et ´evolutifs pour l’analyse biom ´edicale

Reference 22

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Observation be3d7aac-5193-4391-a26c-c11904db7825 · outbound

This paper cites Medclip-sam: Bridging text and image towards universal medical image segmentation.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Medclip-sam: Bridging text and image towards universal medical image segmentation

Reference 23

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This paper cites MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation

Reference 24

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This paper cites Biomedcoop: Learning to prompt for biomedi- cal vision-language models.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Biomedcoop: Learning to prompt for biomedi- cal vision-language models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.554056Z

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Observation 5530fa08-8ceb-4708-b996-44853fc5b4b0 · outbound

This paper cites Be- yond adapting sam: Towards end-to-end ultrasound image segmentation via auto prompting.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Be- yond adapting sam: Towards end-to-end ultrasound image segmentation via auto prompting

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.541927Z

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Observation 89331063-335e-44bc-8920-e8705eedc86e · outbound

This paper cites Semi-supervised segmentation of pancreatic tumor in ul- trasound images with multi-task consistency learning.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Semi-supervised segmentation of pancreatic tumor in ul- trasound images with multi-task consistency learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.529650Z

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Observation e88ff320-ff41-4e82-97cc-a69e52e90214 · outbound

This paper cites Decoupled Weight Decay Regularization.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Decoupled Weight Decay Regularization

Reference 28

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Observation db5413e5-9dd9-4463-94fb-3bac5c1dacea · outbound

This paper cites A deep learning framework for pancreatic tumor segmentation in ultrasound images.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound A deep learning framework for pancreatic tumor segmentation in ultrasound images

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.518651Z

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Observation 416a10c3-834f-4b73-8153-2d7201d06ffa · outbound

This paper cites Segment anything in medical images.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Segment anything in medical images

Reference 30

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Observation 23295c94-659d-4c38-b232-74a76c0e671a · outbound

This paper cites Feasibility and safety of endoscopic ultrasound-guided dif- fusing alpha emitter radiation therapy for advanced pan- creatic cancer: Preliminary data.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Feasibility and safety of endoscopic ultrasound-guided dif- fusing alpha emitter radiation therapy for advanced pan- creatic cancer: Preliminary data

Reference 31

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Observation e81e53af-72f0-4483-ab3d-b8073068a019 · outbound

This paper cites Learning transferable visual models from natural language supervision, 2021.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Learning transferable visual models from natural language supervision, 2021

Reference 32

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This paper cites AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encoder.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encoder

Reference 33

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This paper cites Planification automatique de la trajectoire des ´Electrodes pour la chirurgie de stimulation c´er´ebrale pro- fonde connectomique.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Planification automatique de la trajectoire des ´Electrodes pour la chirurgie de stimulation c´er´ebrale pro- fonde connectomique

Reference 34

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This paper cites Weakly supervised intracranial hemorrhage segmentation with yolo and an uncertainty rectified segment anything model.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Weakly supervised intracranial hemorrhage segmentation with yolo and an uncertainty rectified segment anything model

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.465636Z

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This paper cites Self-prompting large vision models for few-shot medical image segmenta- tion.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Self-prompting large vision models for few-shot medical image segmenta- tion

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.454529Z

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Observation 9c929fb6-1f65-4312-a005-9424e4f30a7c · outbound

This paper cites Am ´eliorer le prognostic neurochirurgical avec l’imagerie multimodale et `a la connectivit ´e c ´er´ebrale.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Am ´eliorer le prognostic neurochirurgical avec l’imagerie multimodale et `a la connectivit ´e c ´er´ebrale

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.444027Z

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Observation 6e00e202-92a5-4a53-9b7b-c4d9ad5fa43a · outbound

This paper cites Advances in medical image seg- mentation: A comprehensive review of traditional, deep learning and hybrid approaches.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Advances in medical image seg- mentation: A comprehensive review of traditional, deep learning and hybrid approaches

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.433128Z

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Observation a1211e34-be94-4d30-9488-03c2e8a3a73f · outbound

This paper cites Customized Segment Anything Model for Medical Image Segmentation.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Customized Segment Anything Model for Medical Image Segmentation

Reference 39

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This paper cites Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

Reference 40

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This paper cites Lungren, Tristan Naumann, Sheng Wang, and Hoifung Poon.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Lungren, Tristan Naumann, Sheng Wang, and Hoifung Poon

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:21:37.421091Z

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Observation c2e151a6-6366-44cf-8482-914ac964ebd8 · outbound

This paper cites BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once

Reference 42

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Observation 8a82bb75-f1d8-4346-abd1-4dea8ed13cb5 · outbound

This paper cites CLIP in Medical Imaging: A Survey.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound CLIP in Medical Imaging: A Survey

Reference 43

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This paper cites Conditional prompt learning for vision-language models.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Conditional prompt learning for vision-language models

Reference 44

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This paper cites Learning to prompt for vision-language models.

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound Learning to prompt for vision-language models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T18:21:37.264892Z

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Pith citing papers

Observation b31418e6-5658-4dfb-b608-ea00b4d1a65c · inbound

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values cites this paper.

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:56:45.976425Z

Source-reported events for the cited work

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