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Paper Citation Record · LEDGER

Mitosis detection in domain shift scenarios: a Mamba-based approach

As of 22 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2508.21033.

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

pith.paper-citation-record.v1
2508.21033 v2

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:38:55.962466Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eef8e4f8-39c4-4360-9fd8-6e320942eda8 · outbound

This paper cites Bertram, Robert Klopfleisch, Natalie ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A.

Mitosis detection in domain shift scenarios: a Mamba-based approach Bertram, Robert Klopfleisch, Natalie ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A

Reference 1

Resolution
metadata mismatch
raw_fallback, observed 2026-08-05T14:38:56.293396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T14:38:54.466250Z digest=sha256:effded962bfa8571f7a81a91af9a2bce2159e29b9ad9700f888641497c0dd3be

Observation db5eb28e-c311-4121-9652-807b381670fa · outbound

This paper cites A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images.Medical Image Analysis, 84:102703, 2023.

Mitosis detection in domain shift scenarios: a Mamba-based approach A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images.Medical Image Analysis, 84:102703, 2023

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:38:58.459249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T14:38:54.556637Z digest=sha256:bf0145378969cadcab38be4f2296b206442232054f7d14beafd84592f6a3ef35

Observation 1c3f9117-9ad5-4317-b310-31549482c678 · outbound

This paper cites Mitosis detection, fast and slow: robust and efficient detection of mitotic figures.

Mitosis detection in domain shift scenarios: a Mamba-based approach Mitosis detection, fast and slow: robust and efficient detection of mitotic figures

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:38:58.114434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T14:38:54.704982Z digest=sha256:feb95628d36d6b8886a235c4824e00e7fd23f3cc02731dbe5da6386c3c6f08cd

Observation a67b3737-7bbe-4c4d-ae2c-cef9bec2d943 · outbound

This paper cites Bertram, Katharina Breininger, Dominik Hirling, Peter Horvath, Nikolas Stathonikos, and Mitko Veta.

Mitosis detection in domain shift scenarios: a Mamba-based approach Bertram, Katharina Breininger, Dominik Hirling, Peter Horvath, Nikolas Stathonikos, and Mitko Veta

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T14:38:54.863751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:38:54.863751Z digest=sha256:c8b5745c8447b6e1a870cf637cb0bc84e04305a2d8150164df9ce63e4373134e

Observation e1ac805c-e923-4628-90ce-b259b66cb2cc · outbound

This paper cites Vmamba: Visual state space model.

Mitosis detection in domain shift scenarios: a Mamba-based approach Vmamba: Visual state space model

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:38:57.878820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T14:38:54.966295Z digest=sha256:f465ce7c26888e1dfc047d025ae6dab057212d2633dcdfe8f2b5e160e418ae93

Observation 7eba81eb-56f1-4c9e-8cba-912d80b0713f · outbound

This paper cites Mamba-sea: A mamba-based framework with global-to-local sequence augmentation for generalizable medical image segmentation.

Mitosis detection in domain shift scenarios: a Mamba-based approach Mamba-sea: A mamba-based framework with global-to-local sequence augmentation for generalizable medical image segmentation

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:38:57.660684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T14:38:55.096137Z digest=sha256:10ef54553a9d9fa4f1eda4781af96b1789342faec1e07ba479a5b6a25469703b

Observation 2b7c2a97-fe49-49ec-b945-4434d813cf66 · outbound

This paper cites Nuclick: a deep learning framework for interactive segmentation of microscopic images.

Mitosis detection in domain shift scenarios: a Mamba-based approach Nuclick: a deep learning framework for interactive segmentation of microscopic images

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:38:57.436721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T14:38:55.236201Z digest=sha256:f504087d1ac4cf167e7acfc84130c3060bb301ab45af6f4a98a8367a187ee530

Observation 259365d7-e050-4c97-9e7f-6c68f4e0574f · outbound

This paper cites VM-UNet: Vision Mamba UNet for Medical Image Segmentation.

Mitosis detection in domain shift scenarios: a Mamba-based approach VM-UNet: Vision Mamba UNet for Medical Image Segmentation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T14:38:55.342986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:38:55.342986Z digest=sha256:072a444003f120ae12338df42e6791ee71741f3d2d5d4c33b91ef99a4d6d790b

Observation c971554d-331b-469b-8350-07bf5cf678dd · outbound

This paper cites Imagenet: Constructing a large-scale image database.

Mitosis detection in domain shift scenarios: a Mamba-based approach Imagenet: Constructing a large-scale image database

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:38:57.236783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T14:38:55.486490Z digest=sha256:70ddf02f8cb079abb07d5e960d5fbbd384442a7aa253a6bdf056a63e585034d3

Observation 2a650cfe-146a-4fa0-a1a1-1304a5089f66 · outbound

This paper cites Structure-preserving color normalization and sparse stain separation for histological im- ages.

Mitosis detection in domain shift scenarios: a Mamba-based approach Structure-preserving color normalization and sparse stain separation for histological im- ages

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:38:57.011713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T14:38:55.560225Z digest=sha256:df319e3934ea2189f09035d25532ebda6ec125e680cc37dd9c1dc43e7a648059

Observation f90d0930-b387-4510-9f17-017ec5f1245d · outbound

This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation.

Mitosis detection in domain shift scenarios: a Mamba-based approach V-net: Fully convolutional neural networks for volumetric medical image segmentation

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:38:56.764330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T14:38:55.657765Z digest=sha256:01cd32e1f5c7d627cac35d9c15f12b80f05a423d4a6030492d80842d3ce3e94c

Observation a3266880-3796-4a22-9360-9dea62b8ef08 · outbound

This paper cites Focal loss for dense object detection.

Mitosis detection in domain shift scenarios: a Mamba-based approach Focal loss for dense object detection

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T14:38:55.763890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:38:55.763890Z digest=sha256:353650d7a1d7aa1b131b49aa73c3cfb85cfcd6ddcf31cca3a5434a7adafdf25e

Observation 5cf060c0-2080-4d84-ad18-746e9f173ce4 · outbound

This paper cites Dono- van, Samir Jabari, Mitko Veta, Jonathan Ganz, Jonas Ammeling, Paul J.

Mitosis detection in domain shift scenarios: a Mamba-based approach Dono- van, Samir Jabari, Mitko Veta, Jonathan Ganz, Jonas Ammeling, Paul J

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T14:38:55.828103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:38:55.828103Z digest=sha256:4e7bd9519cae3e500054356cfa41c16a5dc2209003a374b314f819f824204d73

Observation 42cce926-89d9-4ece-82db-51d3a3946b90 · outbound

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

Mitosis detection in domain shift scenarios: a Mamba-based approach U-net: Convolutional networks for biomedical image segmentation

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:38:56.532884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T14:38:55.962466Z digest=sha256:38d9489ce1eeb49a46b9633ff84c8abcea95bb6b22393baa4ae538df15599d1c

Pith citing papers

No inbound Pith citation observations are available.