Paper Citation Record · LEDGER

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation

As of 8 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2509.05809.

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

pith.paper-citation-record.v1
2509.05809 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:01:38.807869Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

15 of 15 outbound references displayed

verified exact3
verified fuzzy11
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 628cefc7-04c7-4668-9af9-39c88d3ad91c · outbound

This paper cites Annotating Ambiguous Images: General Annotation Strategy for High-Quality Data with Real-World Biomedical Validation.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Annotating Ambiguous Images: General Annotation Strategy for High-Quality Data with Real-World Biomedical Validation

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:01:39.057489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 15d30a6b-2a54-4f7e-a96d-cf9222525734 · outbound

This paper cites Is segmentation uncertainty useful?,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Is segmentation uncertainty useful?,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.148429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cdb06e59-f856-43cd-a2da-b3689cc7725a · outbound

This paper cites Segment anything,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Segment anything,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.140633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f02db15a-9cd1-4116-bb54-ddc504e68709 · outbound

This paper cites Annotation-efficient task guidance for medical Segment Anything,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Annotation-efficient task guidance for medical Segment Anything,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.132721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7081a4cd-fcf1-4777-9e32-7620f68e725a · outbound

This paper cites Detection of Breast Cancer Lumpectomy Margin with SAM-incorporated Forward-Forward Contrastive Learning.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Detection of Breast Cancer Lumpectomy Margin with SAM-incorporated Forward-Forward Contrastive Learning

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:01:39.045787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ba86c359-66a8-4574-b911-bd625e7c1f38 · outbound

This paper cites Autoprosam: Automated prompting sam for 3d multi-organ segmentation,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Autoprosam: Automated prompting sam for 3d multi-organ segmentation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.124827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3833bfc1-e18f-44a7-af38-337aa085b3b9 · outbound

This paper cites Autoadaptive medical Segment Anything Model,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Autoadaptive medical Segment Anything Model,

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-08-05T05:01:39.031363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f1b49351-4242-48c5-aaa1-00b88d5f7c54 · outbound

This paper cites Segment anything in medical images,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Segment anything in medical images,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.116976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 753c38fc-f240-47ca-a82f-2288dcdb9b8d · outbound

This paper cites Flaws can be applause: Unleashing potential of segmenting ambiguous objects in SAM,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Flaws can be applause: Unleashing potential of segmenting ambiguous objects in SAM,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.108606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 585eedce-9bf6-4aaa-90c5-387f0c92d542 · outbound

This paper cites Trustworthy clinical AI solutions: A unified review of uncertainty quantification in deep learning models for medical image analysis.,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Trustworthy clinical AI solutions: A unified review of uncertainty quantification in deep learning models for medical image analysis.,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.100272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f8e06537-1f67-4fce-adce-f79b11fdb9ac · outbound

This paper cites Learning structured output representation using deep conditional generative models,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Learning structured output representation using deep conditional generative models,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.091741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4014edfb-5294-45df-a42f-eb262507acbe · outbound

This paper cites Auto-Encoding Variational Bayes.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Auto-Encoding Variational Bayes

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T05:01:38.799545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a66b50f-d828-4320-a2d5-5fd88e1897e5 · outbound

This paper cites The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A completed reference database of lung nodules on CT scans,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A completed reference database of lung nodules on CT scans,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.082960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 84059758-8943-4c1b-821b-49ecb9171b36 · outbound

This paper cites A probabilistic U-Net for segmentation of ambiguous im- ages,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation A probabilistic U-Net for segmentation of ambiguous im- ages,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.074198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 38580d0f-970a-4e57-808d-d4ac986c56c2 · outbound

This paper cites Energy statistics: A class of statistics based on distances,.

A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation Energy statistics: A class of statistics based on distances,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:01:39.065953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.