Paper Citation Record · LEDGER

Assessing the generalization performance of SAM for ureteroscopy scene understanding

As of 21 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2505.17210.

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

pith.paper-citation-record.v1
2505.17210 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:53:09.870110Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

17 of 17 outbound references displayed

verified exact0
verified fuzzy13
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 93a9808d-d202-4a57-95e1-ccc7831586a7 · outbound

This paper cites an unresolved cited work.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:53:13.009903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6293b672-d048-40b0-b9a2-128729f313b8 · outbound

This paper cites Prevalence, incidence, and determinants of kidney stones in a nationally representative sample of us adults.JU Open Plus, 2(1):e00006, 2024.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Prevalence, incidence, and determinants of kidney stones in a nationally representative sample of us adults.JU Open Plus, 2(1):e00006, 2024

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:12.758209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 75e128ff-2aed-4529-b36b-d104c9aacf2f · outbound

This paper cites Re- currence rates of urinary calculi according to stone composition and morphology.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Re- currence rates of urinary calculi according to stone composition and morphology

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:12.522477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c3607e2c-c3ce-4ce5-aae0-bfa99e29ae61 · outbound

This paper cites Clinical value of crystalluria and quantitative morphoconstitutional analysis of urinary calculi.Nephron Physiology, 98(2):p31– p36, 2004.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Clinical value of crystalluria and quantitative morphoconstitutional analysis of urinary calculi.Nephron Physiology, 98(2):p31– p36, 2004

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:12.318969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 16c6e12c-941f-4024-963d-55554eaa3125 · outbound

This paper cites On the in vivo recognition of kidney stones using machine learning.IEEE Access, 12:10736–10759, 2024.

Assessing the generalization performance of SAM for ureteroscopy scene understanding On the in vivo recognition of kidney stones using machine learning.IEEE Access, 12:10736–10759, 2024

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:12.129497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 39a16141-3eb0-413f-b354-d13123683788 · outbound

This paper cites Deep morphological recognition of kidney stones using intra-operative endoscopic digital videos.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Deep morphological recognition of kidney stones using intra-operative endoscopic digital videos

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:11.989944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1be51404-8713-42ca-971d-906ff1a2fab3 · outbound

This paper cites On the generalization capabilities of fsl methods through domain adaptation: a case study in endoscopic kidney stone image classification.

Assessing the generalization performance of SAM for ureteroscopy scene understanding On the generalization capabilities of fsl methods through domain adaptation: a case study in endoscopic kidney stone image classification

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:11.833390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6dff67ff-abc2-4ba9-bf78-9d3b48bd09a4 · outbound

This paper cites Towards automatic recognition of pure and mixed stones using intra-operative endoscopic digital images.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Towards automatic recognition of pure and mixed stones using intra-operative endoscopic digital images

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:11.586270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b7ccf5c2-493e-42dd-a486-329e539ae5a4 · outbound

This paper cites Effective deep learning for semantic segmentation based bleeding zone detection in capsule endoscopy images.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Effective deep learning for semantic segmentation based bleeding zone detection in capsule endoscopy images

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:11.333252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 529789bf-fd45-41c7-b074-05860c8853dd · outbound

This paper cites Assessing deep learning methods for the identification of kidney stones in endoscopic images.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Assessing deep learning methods for the identification of kidney stones in endoscopic images

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:11.081979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 05f43724-0107-4314-80db-aa5f9aa3b9f8 · outbound

This paper cites Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:10.717552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b7f52cd2-cf0f-487e-8fcc-33addd2ff272 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Assessing the generalization performance of SAM for ureteroscopy scene understanding U-net: Convolutional networks for biomedical image segmentation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:53:09.440082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76884278-c959-49bb-a912-deba32479ad7 · outbound

This paper cites Recurrent residual u-net for medical image segmentation.Journal of medical imaging, 6(1):014006–014006, 2019.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Recurrent residual u-net for medical image segmentation.Journal of medical imaging, 6(1):014006–014006, 2019

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:10.414556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8ad06447-62ea-4eb9-91a6-85c604918545 · outbound

This paper cites Residual-attention unet++: a nested residual-attention u-net for medical image segmentation.Applied Sciences, 12(14):7149, 2022.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Residual-attention unet++: a nested residual-attention u-net for medical image segmentation.Applied Sciences, 12(14):7149, 2022

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:10.219302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cbb4eec8-5461-4027-8b56-b0161c543f61 · outbound

This paper cites Segment anything.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Segment anything

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:53:09.682322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3246540e-5581-4080-9cfa-6324818e2a12 · outbound

This paper cites Evaluation and understanding of automated urinary stone recognition methods.BJU Int., 130(6):786–798, 2022.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Evaluation and understanding of automated urinary stone recognition methods.BJU Int., 130(6):786–798, 2022

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:53:10.032609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d06f9dd7-8b72-4085-b162-b0a4063148da · outbound

This paper cites Classification of stones according to michel daudon: a narrative review.

Assessing the generalization performance of SAM for ureteroscopy scene understanding Classification of stones according to michel daudon: a narrative review

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:53:09.870110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.